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If Dogs Run Free, Then Why Not We?

Dean Howard Smith

Northern Arizona University

July 4 1999

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Chapter 4

If Dogs Run Free, Then Why Not We?

The dogs and pigeons fly up and they flutter around,

A man with a badge skips by,

Three fellas crawlin’ on their way back to work,

Nobody stops to ask why.

Then why not we? The human voice. The human soul. The human inquisition. The beauty, the meaningfulness and the questions of civilization. What can we be, what can we see, and what must we be? We use the tools of language, music, mathematics and visual expression in an attempt to answer these questions.

Then why do we? Pure evil. Desperation, starvation, mutilation, depravation and humiliation. Fifty young women and girls held captive and brutalized until the rumble of the oncoming “peacekeepers’” caravan cause the “soldiers” to dump the girls’ naked and mutilated bodies down the town’s wells.

How do we decide what to do and what not to do? Decisions can be as simple as which pair of shoes to wear or as complex as going to war. Billions of people make thousands of decisions everyday. We make these decisions individually, within family groups, at work, within our communities and within the global community. But the question remains how are these various decisions made?

In an article in 1999, as the millenium was about to turn, in a series of articles discussing “Reconstructing America’s Moral Order” in The Wilson Quarterly Paul Berman wrote:

In the last 20 years or so, and especially in the last 10, the world has undergone a set of very different experiences, good and bad, which are bound to cast a newer light on the old questions about universal destiny. It has become obvious that, all over the world in our present age, only one kind of economic system is capable of producing significant wealth – the system of regulated markets. … It has become obvious that only one kind of political system, the system of liberal democracy is capable in our present age of producing governments of great power and stability, and of inspiring imitation all over the world, as every continent can attest.

The combination of regulated markets and a liberal democracy allows for society to make decisions. As Berman points out, social evolution has proven that this combination is likely to be the only workable combination at present. The complex interactions of the global community at the turn of the millennium led us to the conclusion that individual consumers and producers making their own decisions in the context of regulated markets allows for the production of wealth. Similarly, representative democracy based on one vote per citizen allows societies to make decisions effectively and provide for stability. As Berman points out, more and more countries have been discovering this reality.

In order to understand how these decisions are made in a Social Democracy, it is important to understand how each system works. First, let’s look at a simple model of decision making. Imagine a simple world where we have to make decisions between the production and consumption of two items: art work and luxury cars. Our society has to decide how much of each good to produce.

We can conceive of this simple model by defining the Production Possibilities Frontier, or the PPF. The PPF shows all combinations of goods that a society can produce when all resources are used with maximum efficiency. The PPF is a concept that allows us to imagine the ideal. In our simple model we will use only two goods, but the concept of the PPF can be applied to any number of goods.

A resource is anything that can be used to produce something else or consumed directly. Examples of resources are natural resources like oil or intermediate resources such as steel.

When we discuss efficiency, we mean that resources are being used as well as possible. Technically, we define the production process as efficient when the amount of output is the maximum possible output given the resources being used. Resources are being used wisely and without waste.

Resources not being used are unemployed resources. The unemployment rate measures the number of unemployed people as a measure of the success of the economy, but other resources can also be unemployed if they are not used.

So, when society is using all available resources as efficiently as possible, then it can be said that society is on the PPF.

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Global Warming by 2 Degrees

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Figure 1

In Figure 1, the two goods are luxury cars on the horizontal or X-axis and art work on the vertical or Y-axis. The PPF is shown with points A and B indicated. These points show the important concept of opportunity cost. Opportunity cost is the value of the next best foregone –what is given up - alternative. Obviously, in our two good world, in order to produce more luxury cars society must give up some art work and vice versa. In a more realistic world, the idea of opportunity cost is more involved.

Imagine you have $20 which is exactly the sale price of the new double CD by Limp Bizkit. You could spend your $20 on this CD or something else. You might consider the next best alternative as buying the new Korn CD. Your roommate might think the next best alternative as taking a date to the county fair. Your professor might think it would be nice to take the family out to McDonalds for dinner. Just how the next best alternative is evaluated depends on the individual.

Consider these examples. During graduate school, I won a teaching award which included a $500 prize. I contemplated the decision of purchasing either a CD player or a VCR. After looking at the various prices, and realizing that either machine would also involve purchasing CDs or video tapes, I bought a new set of golf clubs.

After my father passed away, I tried to set up a scholarship fund at my father’s alma mater. However, Canadian law would not allow the scholarship to be limited to high school graduates from the family reservation, so I bought a truck instead.

The idea of opportunity cost is central to the study of economics and the process of decision making. The PPF shows the possible choices that society has available. In order to make a rationale choice, the various possibilities must be examined. Let’s take a closer look.

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Figure 2

Figure 2 shows the same PPF as above. Point A shows one possible combination of cars and art work: L1 and W1. Point B shows another possible combination of cars and art work: L2 and W2. Let’s say society is currently producing at point A, but prefers to have more cars. The opportunity cost of L2-L1 cars is measured by the difference W1-W2. Without going into all the technical details, it is known that society typically faces increasing opportunity costs. The Law of Increasing Costs indicates that as society produces more and more of one good, it must give up more and more of the other good for each unit of the first good. In other words, the opportunity cost increases as more of one product is produced.

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Figure 3

In Figure 3, a third Point C is indicated. The difference between L2-L1 and L3-L2 is the same number of cars, but notice how the difference between W1-W2 is smaller than between W2-W3. This shows that the opportunity cost of cars increase as more cars are produced. Thus the PPF has a curvature to it where the slope gets increasingly steep as more and more cars are produced.

The PPF shows some other interesting ideas: attainability, unemployment and inefficiency.

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Figure 4

Figure 4 shows points A-D. Points A and B are both on the PPF. In other words, these are available options where all resources are being used efficiently.

Point C is outside the PPF: this point is unattainable given the available resources and technology. Society could produce either combination L1 and W1 or combination L2 and W2 but not combination L2 and W1. Since the PPF shows all points that are efficient, points outside the PPF are unattainable to society. Either additional resources need developing or better production methods need inventing.

Point D is inside the PPF. This combination, L1 and W2, is available to society, but it is not desirable. Society could produce more cars and move to Point B, or it could produce more art and move to Point A, or it could produce more of both and move to some point between the two - or any other point on the PPF. Point D shows that one or two things must be true: either society has unemployed resources and/or resources are being used inefficiently.

This simple two dimensional world does not include time as a decision variable. More advanced modeling allows for the introduction of time and the concept of sustainable harvesting of resources. So, in the current context, being inside the PPF does not mean we are saving resources for later.

Thus the PPF points to two important questions that society must answer. 1) how does society structure a production system such that production is pushed out to the PPF and 2) where on the PPF does society locate? These are the fundamental questions that any society must answer. The structure of the political system and the economic system determine the production methods and production choices made by society. If the political and economic systems combine to push the production system toward the desirable answer to these two questions, then the combination is a good one. If the combination of the political and economic systems results in unemployment, inefficiency or an undesirable combination of output, then the social structure is similarly undesirable and needs replacing. As Berman points out in the quote above, the combination of a regulated market economy and a liberal democracy appears to be the combination needed as the millennium turned.

A regulated market economy is one where individual producers make their own decisions within the scope of various regulations and restrictions. The government does not tell the individual producer what to produce or how to produce the output. Regulations and restrictions may limit what can be produced or how items can be produced, but no one tells anyone how to produce what. The regulations or restrictions may limit how items are produced by restricting certain labor practices, such as minimum wage and child labor laws, or environmental actions, such as the Clean Air and Clean Water Acts. Other restrictions may limit what can be produced. For instance, you couldn’t start building nuclear bombs in your basement. Some restrictions limit who can produce various goods and services. For instance, you have to meet certain qualifications before you start selling your services as a heart surgeon. Finally, zoning laws may restrict where certain items are produced. For instance, liquor stores cannot be located next to schools. But as long as the producer follows those rules, anything that comes to mind can be produced and offered for sale.

In a regulated market economy producers are said to be profit maximizers. The purpose of the business is to make as much money as possible given the regulations and restrictions. For the most part, this quest for profit is beneficial for society because it leads to efficiency and full employment of resources. As will be discussed below, when the quest for profits leads to detrimental results, regulations and restriction may be put into place via the political system.

How can greedy money-grubbing business people be good for society? Recall Point D in Figure 4. When resources are being used inefficiently, the business is spending more on resources than is necessary. Recall, at Point D, the same resources can be used to produce more “stuff”. An alternative way of looking at this point is to say the same amount of “stuff” can be produced with fewer resources, and thus at a lower cost.

Since producers are all trying to attract customers, a firm that is being inefficient faces higher costs than its efficient competitors. So either the firm must charge a higher price to cover these costs or its price does not cover the cost of production. If the firm charges a higher price, it will loose customers and eventually have to quit the business. If the firm charges the same price as the competition, but this is not enough to cover cost, then the firm will also have to go out of business. The only option the firm has, if it wants to stay in business, is to redesign the production process and become efficient.

Another way of thinking about efficiency is to say the firm is producing its output at the lowest possible cost and is therefore able to charge the lowest possible price. Since all firms in a regulated market economy are searching for profits, they are also searching for efficiency. In other words, the competition between firms in a regulated market economy pushes society out toward the PPF.

But what about when firms go out of business and resources become unemployed? Well, remember, there are few restrictions placed on what firms can produce, so someone is going to realize that resources are not being used and will come up with an innovative idea to use them. One of the best examples of this process is the recycling industry. As little as 20 years ago, plastic bottles and aluminum cans were simply viewed as trash. These things were not viewed as resources, they were simply discarded. But then some enterprising individuals thought about it and realized that used plastic bottles could be a resource to produce other items. The limited restrictions placed on individual entrepreneurs in a regulated market economy allow for creative uses of unemployed resources, which also pushes society toward the PPF.

The quest for profits within a regulated market economy is beneficial for society. This quest forces firms to be efficient. It also leads creative minds to recognize the potential uses of unemployed resources. Thus, the quest for profit by individual firms pushes society toward the PPF.

But that leaves the other question: where on the PPF does society want to be? Recall Points A and B in Figure 4. Let’s say the individual production decision by the existing firms results in combination B being produced, but society really wants to be at Point A. In other words, the customers of the producers want more art work and fewer cars. Well, since people want more art work than is currently available, they start to fight over it. In a market economy, this “fight” means they start to offer higher prices to the producers due to the shortage. Simultaneously, people aren’t buying all the cars available. In order to sell their cars, the producers start lowering their prices due to the surplus. Initially, the price of art work will increase and the price of cars will decrease until combination B is sold, but what about next year?

The car producers now realize that they can’t get a high price for their product. The competition between car producers will cause some of them to realize that producing cars is not profitable, so some will decide to quit. At the same time, the market for art work is booming. Profits are at an all time high, so the art producers will start to produce more art work – they will employ some of the newly unemployed resources. This simplified example pushes society away from Point B and toward Point A.

If the producers are producing too many cars and too few works of art, then the market forces will force the production system to make the necessary adjustments. This is how a regulated market economy results in a production mix that is beneficial to society.

One important aspect of the discussion above should be pointed out. Other types of economic systems could result in the proper production methods and the proper production mix. A planned economy, where the government makes all production decisions, could result in society realizing Point A. But our simplified model is static- it doesn’t change. In reality, the conceptual PPF is constantly moving and society’s preferred combination is forever changing.

A regulated market economy is self-adjusting. When the PPF moves or society’s preferred combination changes, the market forces producers to move toward the new preferred point. In other words, a regulated market economy allows for mistakes. If a firm is being inefficient or is producing the wrong stuff, they will be forced to either correct their mistake or go out of business. If they go out of business and resources become unemployed, someone will come along and realize a profit potential for those resources. This is a vital aspect for any production system: allow for mistakes.

Consider the example above. At point B, the production system is being efficient, but society wants more resources devoted to the production of art and fewer resources to the production of cars. If the production system did not allow for corrective adjustments, then the movement from Point B to Point A would never happen. Similarly, if inefficient firms were not allowed to go out of business, the movement from Point D toward the PPF would never happen.

During the 20th Century many countries experimented with planned economies, but almost all have faltered. As indicated, a planned economy could result in the proper outcome, but since the implementation of those plans resulted in mistakes, and those mistakes could not be corrected, the economic systems, the Soviet Union in particular, basically collapsed. As Berman concluded, “It has become obvious that, all over the world in our present age, only one kind of economic system is capable of producing significant wealth – the system of regulated markets.” The experimentation with different types of economic systems has proven this.

Not only did the economic systems fail for countries using planned economies, but in many instances, their political systems also failed. Many decisions are made by society through the economic system, but many others are made via the political system. Let’s explore this idea now.

The conceptual PPF can also be used to understand some of the choices society must make as a societal body as opposed to a collection of individual decision makers.

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Figure 5

In Figure 5, the two options for production are National Defense and Consumer Goods. National defense includes funding for the various branches of the armed forces such as salaries and equipment. These are expenditures society makes as a whole. Individuals pay taxes and the government uses those funds to pay for national defense expenditures. Society must decide how many resources to devote to national defense. The opportunity cost of increasing national defense is a reduction in consumer goods.

In a liberal democracy, this decision is made by individuals deciding whom to vote for. Again, the model is simplified in the extreme, but the conceptual idea still holds. Imagine that the last election revealed society’s preference to locate at Point A. International events result in society desiring additional national defense, such as Point B. Either the elected representatives increase the tax rate to pay for the additional national defense, or they will be voted out at the next election.

In a representative democracy such as the United States, individuals “spend” their votes in local, state and national elections to purchase a combination of goods just as they spend their money in the market economy. In this case the elected representatives are akin to the firms. Their decisions in the legislative body “produce” social outcomes regarding national defense, education, and myriad other types of social resource allocation. Where the simplified model looses its explanatory use is the fact that instead of making individual purchases of cheese, crackers, cars and art, people have to vote for a representative based upon the complex matrix of political issues. But once again, a liberal democracy allows for mistakes. Since elections occur on a regular basis, the results of one election can be corrected in the next election.

The opportunity to correct mistakes is a vital aspect of both the economic and political systems, but as Berman points out, there is also a need for stability. Within the economic system, firms must be able to survive temporary periods of loss. This is accomplished through the credit markets where firms can borrow against future earnings, if they can convince the lenders that those earning will be forthcoming. Within the political system, stability can be achieved via the constitutional structure of the legislative bodies.

In the United States, stability is achieved by having differing lengths of terms for the legislation bodies, Senate and House of Representatives, and the executive branches of government. This stability is further secured by having staggered terms within the Senate and having life-long appointments to the Supreme Court.

Stability is very important within society. There is a huge difference between society making a mistake that requires adjustment and a temporary disruption. If the political system does not allow for correction, such as in a dictatorship, then society will eventually find itself at a point on the PPF other than the desired point, or more likely, inside the PPF. On the other hand, if the system is unstable, then it is impossible to make any plans for the future.

Consider the case of Russia during the Yeltson presidency. During a period of 18 months, President Yeltson fired his cabinet and Prime Minister repeatedly. This instability caused constant confusion within parliament. Instead of concentrating on the important issues of rebuilding – some would argue building for the first time – their society, the politicians focused their efforts on the inner workings of the personnel structure. Additionally, since investors in the economic system were uncertain about the political structure, investments were not being made. Thus, the instability within the Russian political system resulted in a stagnation within their society.

As with the economic system, other political structures could lead society to the desirable result. But when adjustments are called for, dictatorships do not allow for correction and unstable systems result in too much upheaval. A stable liberal democracy allows society to make reasonable decisions.

As Berman points out, the various experiments with economic and political systems resulted in the conclusion that the combination of a regulated market economy and a liberal democracy is the only workable structure that allows societies to make meaningful and rewarding decisions. The simplification of the PPF allows us to understand why this is so.

But the PPF as presented above leaves some important questions unanswered. Again, these can be discussed by changing the focus of the decision matrix. A free market economic system is one where no regulations exist. If society were to have a free market system, various problems would quickly become apparent. When these problems crop up, the political system is called into action to design regulations that alleviate the problems.

In response to a homework question concerning how societies correct for mistakes in this framework a thoughtful student wrote what was at first a puzzling sentence, but one that carries great wisdom. “We have a government of ‘can’ts’ and not a government of ‘cans.’ Honestly, it took me several readings to figure out what Paul meant. In our regulated market system, we have a list of regulations, as discussed above, that list off things that people ‘can’t’ do. If an entrepreneurial soul has an idea and that is not listed, then we say – as a society – go ahead and try it out. If it works and people like the new idea, then the entrepreneur will make money and stay in business. If the idea basically sucks, the business will disappear and the resources will be freed up for other ideas.

The beauty of Paul’s comment is the counter example he offered. If our society was one of ‘cans,’ then there would simply be a list of things that are allowed. New ideas would not be allowed to be explored and new production technologies or new products would not bear any fruit. As will be discussed in detail in later chapters, the very creativity of the human spirit – within the context of regulations – will be the driving force of finding a way out of the quandary of climate weirding. Imagine having to pick from a list of allowable activities!

Our area of major concern is the interaction of human activity with the environment.

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Figure 6

In Figure 6, the PPF has been redesigned to show the choices between a clean environment and consumer goods. One of the realities of the drastic increase in production during the last 200 years is the fact that much of this production results in pollution of one sort or another. It would be a simple matter of closing all factories and outlawing internal combustion engines if society desired a perfectly clean environment. But the opportunity cost of doing so would be the consumer goods we now produce – including food.

Because the idea that human action has negative effects on the environment is relatively new to our human experience, it could be convincingly argued that industrial society is currently at a point inside the PPF such as the previous point D. This new realization has led to a variety of new regulations like the Clean Air and Clean Water Acts. Since these laws were passed less than 40 years ago, great strides have been made in terms of efficiency – pushing out toward the PPF. The amount of pollution per unit of output has drastically decreased as firms have found new and better ways of producing their stuff. A following chapter will explore the specifics of policy design, as for now, the presentation remains very simplified.

Recall the conceptual idea behind the PPF. Now that gains in efficiency are becoming harder to achieve, society is now faced with the question of where on the PPF to locate. This involves serious choices at both the economic and political levels.

Within the realm of a regulated market economy, the interaction of consumers and producers has resulted in more and more products being produced with environmentally safe methods. Many firms have gone beyond the strict requirements of various environmental laws and use this fact in their advertising campaigns. As the environmental consequences of our modern production techniques have moved from the back pages of scientific journals to the front pages of newspapers, consumers have also begun to change their behaviors. Consumers are demanding products that are produced in environmentally friendly ways and new kinds of products that have low impacts on the environment. These so-called “green production” changes in the market place have resulted in a movement along the PPF.

But the market place can only do so much on its own. This is why we have regulations. The political system has a role to play as well.

Let’s explore the problems with global warming and the choices that global society has to contemplate. In order to understand some of the issues revolving around global warming, we need to introduce another investigative methodology: hypothesis testing.

A hypothesis is an assertion subject to verification. Therefore, hypothesis testing is the process of evaluating assertions that may or may not be true. However, analysis of this type is not simple. The question concerning global warming, for example, is a very complex one. Does the human production of carbon dioxide and other gases actually cause a warming of the atmosphere? If so, how can this be proven? Unfortunately, in most cases of complex inquiry definitive proof cannot be developed – and global warming is a strong example of this. So instead of collecting definitive evidence, the problem becomes one of collecting convincing evidence.

Hypothesis testing is a methodology used in a variety of disciplines based on statistical analysis. The first step in conducting a test is to determine what is called the null hypothesis. The null hypothesis is a statement indicating what will be evaluated. If the question is a mathematical one, there are specific rules regarding the formulation of the null hypothesis, but for our current purposes we’ll simply focus on the concept. The alternative hypothesis is simply what ever disagrees with the null hypothesis. For our example, the null hypothesis is that human production of carbon dioxide results in global warming. Therefore, the alternative hypothesis is the statement that global warming is not due to human activity. Of course the IPCC and many other have pretty definitively answered this question by now.

Recall, a hypothesis is simply an assertion. As such four possible results can occur from the test. Based upon the available evidence, we either reject the null hypothesis or fail to reject the null hypothesis. If we reject, then we conclude that the statement is probably wrong. Since we can never know for certain, we can never say the null hypothesis is true; rather we can say that we fail to reject the null hypothesis. In essence, we are saying that the null hypothesis is probably correct. If we could collect enough information to make a definitive conclusion, we could discern whether the null hypothesis is true of false. The following table shows the possible outcomes.

Actual Reality

Null is True

Null is False

Conclusion from Statistical test

Fail to reject Null Hypothesis

Correct conclusion

Type II error

Reject Null Hypothesis

Type I error

Correct conclusion

If the null hypothesis is actually true and the statistical analysis shows that we should fail to reject, then we’ve made a correct conclusion. Similarly, if we reject the null hypothesis when it is in fact false, then we’ve made a correct conclusion.

But it could also be the case that the evidence is misleading and we make an incorrect conclusion. If the evidence shows that we should reject the null hypothesis when it is actually true, then we are making what is called a Type I error. A Type II error is when we fail to reject when in fact the null hypothesis is false.

Using our example of global warming, the four possible outcomes of our test are easily explained. If the human production of carbon dioxide causes a warming of the atmosphere and we collect evidence that convinces us that this is the case, then we’ve reached a correct conclusion. Conversely, if global warming is not human caused and we are convinced of this, then we are also correct.

The potential problems occur when an error is made. If the statistical evidence leads us to reject the null hypothesis when in fact human production of carbon dioxide is causing global warming, then a Type I error has been made. On the other hand, a Type II error results when we conclude to fail to reject when global warming is not happening.

These mechanical steps of our hypothesis test have serious implications for the types of decisions society makes.

If the evidence convinces us to fail to reject, then we are essentially saying that the human production of carbon dioxide and other gases is indeed causing global warming. This result might well cause society, through the political system, to impose regulations and restrictions on the production processes. These enforced reductions in the human production of carbon dioxide and other gases will change the combination of consumer goods available to consumers. Since the burning of fossil fuels, oil, coal and natural gas, are the primary sources of carbon dioxide, a plethora of changes will have to be made within society’s actions.

On the other hand, if the evidence convinces us to reject the null hypothesis, then the political result will likely be a decision to make no additional regulations. It is important to recognize that a decision to do nothing is a decision.

The political process is complex with regard to the possible outcomes. The possibility that global warming is happening may lead to further regulations and restrictions. This may be reasonable if the event is actually occurring, but a great deal of concern and dogma revolves around the possibility of a Type II error.

What if these restrictions are uncalled for because global warming is quite simply not occurring? The political rhetoric revolving around this possibility is quite strong as will be discussed in the “Bob Williams Chapter.” Obviously, the restrictions will limit the human caused production of carbon dioxide and other so-called greenhouse gases. This has led to an uproar among those industries that are major culprits in the effluent of carbon dioxide. These companies are very concerned, for obvious reasons, about their future profits if the restrictions are enacted.

Although further efficiency gains can be realized, there is little doubt that the restrictions will cause some industries difficulty. In order to reduce the human production of carbon dioxide and other greenhouse gases, Schelling made an early estimate of a reduction of 2% of Gross Domestic Production in the United States.

A 2% reduction in GDP would be roughly equivalent to less than one year’s growth. Although it varies year to year, GDP typically grows by 3-4% annually. So reducing the effluent of greenhouse gases will not require a drastic change in the overall production system. However, the required changes will not hit all industries equally.

The industries that are most likely to face substantial restriction, and therefore reduced profits, are vigorously using the political system to avoid the implementation of such regulations. Using various lobbying techniques representatives of these industries are using a Type II error argument: there is no convincing evidence that global warming is a problem. Furthermore, they argue that even if global warming exists the effects won’t occur for many years.

But what about a Type I error? If the evidence is such that global warming does not appear to be happening, when in fact it is happening, then no restrictions will be enacted. Alternatively, if the political process results in a lack of regulation when in fact global warming is occurring, then what are the consequences?

One day I had just finished teaching this hypothesis testing material to a class and was driving home listening to Science Friday. This must have been the spring semester in 2000, but I may be wrong. The topic that day was exactly the one under discussion herein: climate change. Those were the very skeptical days of the discussion, and obviously much of the conversation before I turned on the radio had dealt with what we are calling a Type II error – the consequences of creating regulations when no regulations are in fact needed. The next caller into the show asked “What if we make a Type I error?” I almost put the car in the ditch in utter surprise. I swear that is true even if I don’t remember the precise show. The caller went on to discuss what might happen if we fail to create new regulations and ideas and climate change arrives.

Of course, the Stern Report, the IEA and the IPCC have thoroughly investigated and statistically quantified the consequences of a Type I error, and these estimates will be discussed below. But for the current chapter, let’s continue with the example.

It is clear that weather patterns will change. In many locations, these changes will be detrimental, but in other locations, the changes will be beneficial. The warmer weather and changes in precipitation patterns will actually improve agricultural output in some locations such as central Canada.

Obviously some countries, particularly island nations, are very concerned about the possibility of rising sea levels. There appears to be increasing evidence that the fluctuations in weather patterns are increasing in terms of drought, flood, and the severity of storms. Additionally, the very uncertainty concerning the possible effects causes some people to argue that this might be the worst aspect of the situation. Borrowing from Richard Norgaard’s work, global warming is a “large experiment” with unknown results, and therefore should be avoided .

Let’s introduce a couple of new measures. One measure that is commonly used is the average. In statistical analysis, this measure is called the mean. Another useful measure is called the standard deviation. This is a measure of dispersion, which shows how the data values are scattered. The larger the standard deviation, the more scattered the values are, and the smaller the standard deviation, the more clustered the data.

image7.jpg Let’s compare the weather patterns when global warming occurs. Imagine a location where the average temperature is 70 degrees with a standard deviation of 10 degrees. Now let’s increase the average temperature by 2 degrees due to global warming. We can look at a graph of these two situations.

Figure 7

The dashed curve shows the higher temperature scenario. Since the average has increased by two degrees, the curve has simply shifted to the right and the result is more days with high temperatures and fewer days with low temperatures. This is the reason why locations in the extreme northern and southern latitudes may actually benefit from global warming: improved weather patterns.

But the evidence points toward increased variability in weather patterns as well. This increased variability results in an increased standard deviation. Let’s compare the original scenario of an average of 70 degrees with a standard deviation of 10 degrees with a situation where both the average and the standard deviation increase by 2 degrees. The following graph shows the result.

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Global Warming:

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Figure 8

In this scenario, not only does the number of warm days increase, but the number of cold days also increases! The increase in the standard deviation – the variability of the data – has severe effects on the weather patterns. If it were simply the case of an increased average, then it might simply require a change to more heat resistant crops as the temperatures increase. But the increased variability will require crops that are both heat and cold resistant. This type of possible result adds to the uncertainty factor regarding global warming.

This brief overview of hypothesis testing and statistical analysis allows an understanding of the controversies revolving around global warming. But another aspect of the situation further complicated the decision process: the influences are global in nature.

Pollution can have local, regional or global effects on society. For example, air pollution caused by automobiles in Phoenix Arizona degrades the air quality in the local Phoenix area. This pollution is augmented by sources such as Los Angeles and the Mohave Generating Station as a factor in the haze problems at the Grand Canyon. The greenhouse gases produced in Phoenix also contribute to global warming.

Since pollution has local, regional and global effects, decisions have to be made at a variety of levels. As the scope of the causes increase – local to regional to global – the political process becomes more complex. Global warming is especially problematic since the scope potentially involves literally every national and international political body in the world.

The Kyoto Treaty negotiations involved over 150 national governments trying to agree on limitations for the human production of greenhouse gases . The upcoming Copenhagen negotiations, 2009, may result in an updated agreement. Then the United States will have to decide to ratify the new agreement – we never ratified Kyoto. When ratification does occur, then the production system will have to make changes based upon the form of regulations enacted. The interaction between the economic and political systems will result in a combination of goods somewhat different than those being produced today. The political structure of a liberal democracy leading a regulated market economy will allow the decisions to lead to an efficient and desirable solution. Since more and more countries are adopting this combination of decision systems, the global solution regarding the human caused production of greenhouse gases will move toward the socially preferred result.

So if dogs run free, then why not we? Well, in most industrial societies with high population densities, dogs don’t run free. Socially determined regulations concerning leashes and fences limit the freedom of dogs. In the same manner, regulations and restrictions limit human behavior. But as long as the dogs stay within their fenced areas, they can chase butterflies as the wind blows. The same is true for humans living with the combination of a liberal democracy and a regulated market economy: creativity and entrepreneurial activity stimulates efficiency and socially desirable results. We can do it both better and smarter. We must do so.

� EMBED Excel.Sheet.8 ���

� EMBED Excel.Sheet.8 ���

� Most of this chapter was originally a paper of the same title written on July 4, 1999 as a teaching device for a freshman level course being taught on air pollution with my grand colleagues Bruce Fox, Janet McShane and Marin Robinson. Since then the original paper has been very helpful in introducing economic analysis to numerous classes. I have updated it for current purposes. The opening paragraphs refer to my thinking about the terror of the Bosnian “troubles.” Keep in mind that Economics has been known as the Dismal Science since the Malthusian quandary. Keep in mind the paragraphs on Bosnia when we get to the chapter on migration.

� The title of this article comes from “If Dogs Run Free” and the quote is taken from “Three Angels”, both by Bob Dylan. See Lyrics, 1962-1985, Bob Dylan, New York: Knopf, 1985, pages 290 and 296 respectively.

� Berman, Paul, “Reimagining Destiny,” The Wilson Quarterly, Summer 1999, Vol XXIII, Number 3, pages 45-55. See specifically pages 45-46.

� A vital consideration at this point is that the firm in question is producing the same quality of product as the other firms. If a firm was producing lesser quality cars, then a third axis would be necessary in the graph since a third good would be available.

� Oh my, how much has changed since I first wrote this paragraph! Recall the original audience was freshman in 1999. With newer information, this example could be updated, but I will do so in the text.

� Schelling, Thomas C., “Some Economics of Global Warming,” The American Economic Review, Vol. 82, No. 1, March 1992, 1-14.

� Norgaard, Richard B., Development Betrayed: the End of Progress and a Coevolutionary Revisioning of the Future, New York: Routledge, 1994.

� I am still puzzled how I foresaw this as a possible outcome when the data were still uncertain.

� See Cooper, Richard N., “Toward a Real Global Warming Treaty,” Foreign Affairs, Volume 77, No. 2, March/April 1998, 66-79. This very readable article explains many of the issues surrounding the Treaty negotiations.

18

2

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max 100.1573891193 45
min 42.3055225331 50
average 70.2506411761 55
60
65
70
75
80
85
90
95
100
105

Sheet5

Bin 72,10
45 5
50 8
55 31
60 76
65 149
70 163
75 201
80 144
85 120
90 66
95 25
100 8
105 4
More 0

2degrees

70,10 72,10 70,10 70,10 72,10 72,12
45 0.0062096799 0.0034670231 0.0122244334 0.0062096799 0.0034670231 0.0122244334
50 0.022750062 0.0139033989 0.0333764484 0.0165403822 0.0104363759 0.021152015
55 0.0668072288 0.0445654318 0.0782902521 0.0440571668 0.0306620329 0.0449138037
60 0.1586552598 0.1150697317 0.1586552598 0.091848031 0.0705042999 0.0803650076
65 0.3085375326 0.2419635785 0.2798344171 0.1498822729 0.1268938468 0.1211791574
70 0.4999999998 0.4207403128 0.4338161627 0.1914624671 0.1787767343 0.1539817456
75 0.6914624674 0.6179113575 0.5987062738 0.1914624676 0.1971710446 0.164890111
80 0.8413447402 0.7881446661 0.7475075327 0.1498822729 0.1702333086 0.1488012589
85 0.9331927712 0.9031994505 0.860669717 0.091848031 0.1150547844 0.1131621843
90 0.977249938 0.9640697345 0.9331927712 0.0440571668 0.060870284 0.0725230542
95 0.9937903201 0.9892759189 0.9723599219 0.0165403822 0.0252061845 0.0391671507
100 0.9986500328 0.9974448094 0.9901846931 0.0048597126 0.0081688904 0.0178247713
105 0.9997673266 0.9995165175 0.9970201814 0.0011172938 0.0020717081 0.0068354883
110 0.999968314 0.9999276276 0.9992289495 0.0002009873 0.0004111101 0.0022087681

2degrees

&A
Page &P
70,10
72,10
temperature
probability measure
Global Warming by 2 Degrees

stdev2

70,10 72,10 70,10 70,10 72,10 72,12 70,10
45 0.0062096799 0.0034670231 0.0122244334 0.0062096799 0.0034670231 0.0122244334 0.0062096799
50 0.022750062 0.0139033989 0.0333764484 0.0165403822 0.0104363759 0.021152015 0.0165403822
55 0.0668072288 0.0445654318 0.0782902521 0.0440571668 0.0306620329 0.0449138037 0.0440571668
60 0.1586552598 0.1150697317 0.1586552598 0.091848031 0.0705042999 0.0803650076 0.091848031
65 0.3085375326 0.2419635785 0.2798344171 0.1498822729 0.1268938468 0.1211791574 0.1498822729
70 0.4999999998 0.4207403128 0.4338161627 0.1914624671 0.1787767343 0.1539817456 0.1914624671
75 0.6914624674 0.6179113575 0.5987062738 0.1914624676 0.1971710446 0.164890111 0.1914624676
80 0.8413447402 0.7881446661 0.7475075327 0.1498822729 0.1702333086 0.1488012589 0.1498822729
85 0.9331927712 0.9031994505 0.860669717 0.091848031 0.1150547844 0.1131621843 0.091848031 Weather Days with 50 degrees or less Days with 90 degrees or more
90 0.977249938 0.9640697345 0.9331927712 0.0440571668 0.060870284 0.0725230542 0.0440571668 70,10 2.3% 6.7%
95 0.9937903201 0.9892759189 0.9723599219 0.0165403822 0.0252061845 0.0391671507 0.0165403822 72,10 1.4% 9.7%
100 0.9986500328 0.9974448094 0.9901846931 0.0048597126 0.0081688904 0.0178247713 0.0048597126 72,12 3.3% 13.9%
105 0.9997673266 0.9995165175 0.9970201814 0.0011172938 0.0020717081 0.0068354883 0.0011172938
110 0.999968314 0.9999276276 0.9992289495 0.0002009873 0.0004111101 0.0022087681 0.0002009873

stdev2

&A
Page &P
72,12
70,10
Temperature
probability measure
Global Warming: Mean and STDEV by 2 Degrees

Sheet3

72,12 59.6081801631 71.0788228388 98.8808071269 77.0966445997 71.5330881575 66.9836274027 79.5990737969 70.8908712112 75.5011225918 68.0101922625
67.9480646794 69.2152818373 62.405231074 70.1619293976 56.7422623134 82.2551848613 93.3376733882 61.6132612776 68.342439772 77.4372958402
63.4889031061 77.0504650062 60.0065661273 72.383324732 103.2470365316 62.3419029579 61.3299900577 53.3025715412 72.987479325 84.2905657918
61.0489834797 69.4542834025 65.8478003969 70.5400290825 65.4954439595 63.9777110335 69.1114493746 88.790600057 81.8586951935 69.0499902702
88.1820935318 81.0266439656 67.4320128381 76.0354279918 78.9623001764 64.873008523 84.0875938592 83.7998479254 51.2557719047 73.6099147615
55.2629873708 71.7792110662 62.8547488303 81.6377971204 68.2037236401 74.7988517104 46.8467598693 113.127204895 66.5769468468 86.7190803546
41.2192068323 69.8846199156 80.4710154624 78.6592747316 64.9276873445 56.5591810299 62.8694553596 57.4604266147 54.9034550203 72.8420238373
88.7979123944 77.9364720073 72.610252755 61.0239087108 72.3539389581 81.345358194 55.1702189113 76.5127626436 78.2193066697 68.7033636494
95.5144034377 56.9702271604 91.9083297048 74.1909454517 57.8118280827 55.7859832041 67.3212773107 74.4031805879 81.939976735 55.6685492483
85.9472740557 73.85479621 78.7881546784 48.2167863082 59.2764510656 54.7139072295 74.5156759875 58.4299934416 85.7915321829 61.9261638348
86.7894206748 63.7105651548 57.9220315557 73.3924818631 48.0845093988 56.2211764189 74.4088012651 88.3919139595 68.3684012982 73.336125024
89.9804374056 88.5949404618 77.0464541346 68.7757639752 75.1766785469 66.4076444081 92.5030301004 78.9742645792 84.4797588796 68.9657073962
82.1826208265 65.9126155368 74.7140231396 55.2944740774 86.4481964526 61.9339945841 85.3547018777 60.1479288888 72.3612785804 88.4457742358
68.2769970807 68.1718549457 72.5395031621 65.9241024549 90.4750570043 75.0968840292 81.3640210252 77.568836059 66.3205102682 99.5153433904
98.9604788627 57.9165473026 67.2627786115 64.5573365545 81.6276744443 75.7095242078 77.8195291786 52.2463207743 52.000211508 104.9854083247
61.431830727 68.5534470903 65.2957052806 59.4458899285 63.5395846983 67.8858006721 48.8206544104 77.9458034229 100.601498343 49.376392053
58.9396742724 71.567071427 87.0458981807 69.0045610098 88.0913987202 56.9722189538 70.312241587 86.8425442603 90.8440571947 80.1709640654
72.6433492672 85.7773167808 73.4396300685 77.6558747019 64.5662450551 78.5183758124 82.8290805656 76.4566513679 85.7312872539 96.4760303758
98.4787377091 68.7110034049 61.9353042565 64.9440582491 65.3417893772 80.4310158854 76.3035834096 63.2822204351 89.3276748683 68.2095080264
57.4297857382 59.2554963076 66.2670592645 72.8282177077 75.6008623283 92.0330214284 65.7418124318 61.4925804256 63.5583975962 84.8628926177
69.7754396241 81.6403346106 45.9829218015 67.1822883304 100.0789390672 77.9655440054 73.734115358 87.4955796461 100.7446891889 96.2313399212
85.8271389005 63.2929706625 76.4950411393 72.9524865163 64.0521713648 62.6856919552 75.7152949517 90.8850935956 75.9665201257 69.344325493
76.6886270866 65.7260417937 67.5757903081 68.2143374432 77.6990120356 68.4135440678 80.8956221589 75.2366097003 62.1464616414 64.5673500911
70.8752097124 67.3202950564 90.9295678865 88.950925783 76.8127321861 54.9413536645 72.7730068319 80.7548596639 75.2689968066 89.4959677679
67.0726441966 81.7548490885 69.9023277774 84.2163510241 61.125326465 61.8699024925 63.8371395324 80.4627754404 86.1752389027 59.9230745137
55.2191679161 73.0519670468 73.7090678739 76.979347068 68.3462869346 39.6833976991 76.7511093726 52.1279045641 75.3071137295 84.3153949971
69.5940090735 61.8318401392 81.0510366135 75.5586253944 96.1473026108 90.1977338798 66.7704372971 76.9943537306 76.4674834498 77.8515479395
67.066655174 64.4580606603 77.328674888 88.2461037689 66.055233401 80.1640337157 49.8270284878 66.8782260617 75.4934555515 84.8612828121
70.3937959769 72.5725723895 87.2536449605 59.0651299716 64.7058615867 82.573585314 68.1332059684 78.6410757427 69.8510459187 61.0670733294
69.511526999 54.0364791958 47.9629281471 29.7272683382 68.1254707159 66.5036461213 82.143221516 64.8379338598 93.1963924812 74.660381142
57.9911986277 68.4000926411 62.3786556388 82.1222394733 74.2133463062 83.0586552182 66.254712874 81.9567841971 88.3686127053 50.0849248054
66.2227759675 85.9563053381 71.3235542206 82.0842862594 46.1909414297 77.4403381 78.6528491516 64.2951838016 52.9192195244 74.5973804441
98.8583244178 55.9176325622 72.4862022251 73.8798846213 68.0373543217 84.2998699226 98.6166898655 73.0704115994 70.8567651599 51.1318987263
71.8719385985 64.1092512523 43.4766454417 90.6881516129 62.1297223914 83.3453370432 69.4580350681 76.9263599067 65.0594049147 79.3638238973
83.2566613097 73.4784700397 84.1013181342 74.6669567887 88.4059383678 69.7913194016 68.9571808833 71.6883116182 54.0477205503 77.4749489209
77.5616874306 58.3039920456 55.9289012016 79.8247740021 63.9972196949 73.0870007827 56.9258892937 54.2886456968 85.7224742502 79.1994054451
81.7740303318 99.3033947451 88.5782148542 94.4574978347 76.3643331082 75.2309071685 83.9135165733 51.7872260388 67.4389295453 62.7463734417
54.3862708581 62.2897889115 52.1783815201 65.3053641143 62.8915287961 60.3201508055 71.3584788172 71.5560483512 52.0112345838 84.0830100059
82.913472579 86.0834526974 48.2233346701 63.3775536697 64.9963632894 80.5737838162 42.3140929341 56.5065212867 59.3246633797 59.8098151385
83.1827466753 80.9913646661 69.0953922457 72.9082850738 63.3823285169 90.7314799405 76.2273086365 81.2734080681 60.1613803154 73.8455057216
66.1680835036 92.491243049 74.4369046514 81.939976735 59.3438991926 82.8470067062 45.1752905063 61.5369455771 77.4189877119 78.8140207077
99.2064789897 87.328050722 79.0199530455 84.4734560814 69.1312990965 62.8338759269 86.06154297 69.8482492224 61.4845041126 64.4591793388
78.146974556 79.8964512795 60.0864834267 93.4728424908 78.0175352701 79.5195930549 71.9903684511 65.2516675472 86.9516563397 47.1835639472
80.1628604676 86.399029169 45.9152553957 95.3965329244 79.5979551184 93.0580037674 92.7811717701 84.7219391288 65.599399204 76.8107403927
81.4776896731 72.3823970474 65.0376998236 79.3129103839 82.646872397 79.1313843364 77.2366294767 82.135336197 102.0517422147 77.529000191
63.7629247648 92.7156881515 63.4900763542 76.2595593186 79.5263051258 98.9262091024 83.4592239697 66.6064144751 81.3416201707 49.7198536322
74.6895486371 50.5225736559 78.9883981269 90.2326039067 91.9119858735 50.8471541251 71.9398642103 54.8704676474 75.3901551433 65.0474677967
78.1155833464 92.0145223062 85.9364692586 89.8600566869 46.4976230431 66.0063935355 69.3734793457 81.6936764749 61.4453503657 56.0983400645
72.2758770279 56.6594801056 76.5571277951 41.5287260693 73.2170403352 81.7612473837 89.8212576429 91.0872742678 81.079112715 77.8567184169
61.4453503657 56.9521100259 61.1557490628 78.3551306084 78.5652511694 50.67122147 68.9552845869 74.1191044652 84.6401118905 69.790391717
72.2997512638 58.3408811507 67.5767725623 86.2455792229 81.9866065284 77.6435692386 66.3297461868 72.6580557965 58.1478681851 71.935280357
85.8324867294 75.8320058593 56.1005228518 91.3251980818 87.4282133735 59.1793988859 76.4871558202 66.262952896 77.1217739383 66.9535458654
64.4625353742 84.6433042169 85.0040098156 67.1414702082 69.5255923346 51.0100991959 86.6491765918 89.0259045262 69.5133960106 76.4340322347
83.2225006887 61.8449641478 67.0926030579 74.5522786018 93.2888335227 76.7292814997 60.7219473749 58.2545791984 67.0156598061 59.9474398767
83.3109308586 70.4919259077 60.3230975684 66.8127970129 61.5785003901 57.8578848944 73.233643161 44.1157655586 86.2585940921 71.379624569
68.437527443 54.8679028724 82.8857511805 72.6130221664 93.680862119 71.6322958395 66.2886552162 63.2762450549 94.1276241064 79.1851081884
84.171740309 101.9888779409 70.9083880791 71.5790221874 54.5780832907 105.276155591 79.1456270234 86.0051452036 69.4420734361 65.3128674456
64.4121402728 88.198027879 77.78752406 69.172840267 49.2225055494 73.6664216673 50.8340574014 61.0308663453 58.8296072236 59.8082871874
84.9414456751 78.4779942477 53.6500712768 71.3906612872 79.5006028055 50.4493411426 78.3456354837 61.3979565968 61.1640436545 75.6787196223
60.9651917329 100.3559347736 65.7334087008 43.0403062636 84.5906444737 65.3268099994 92.3699892154 85.443732314 68.5352617437 74.3498250812
78.7773908086 84.2781511891 65.9907866064 68.5008009895 59.2102307563 65.1719412416 94.1427399083 50.8297463965 76.3820000428 67.2598045638
65.1989259494 49.4946991238 70.9922480381 74.2535095923 62.4796095507 64.6139935269 56.2603301659 69.2011482896 65.8195196592 118.1004674435
75.1073341233 78.1166338128 65.3674916974 77.222495929 61.354491845 79.4182025855 57.1020402275 72.4347566573 72.5266247172 84.810833141
62.8608879196 60.8738148002 51.0396759636 58.7538917897 79.0058058554 55.694006005 89.4535671249 59.8635389905 45.489830154 90.299833755
81.9141107057 71.7250370143 75.6258279579 104.1140396409 85.7844108394 83.1388999358 85.8396080729 74.2376298148 80.5832652985 65.6131507638
49.892402967 68.4356175042 70.1934979587 57.1277971175 75.026707418 57.4776433494 77.8794739743 85.3308549266 68.0925651976 95.4894105233
74.1778760129 81.1526180768 51.048188834 72.258428372 59.4712648307 59.1972704568 81.196874089 69.9219046509 51.489002726 63.8845060165
79.3882165452 82.3813908936 54.4480164534 59.2069838602 81.991817933 66.3338525554 73.0934536476 67.2081543597 75.6681467463 89.6759931492
68.3876098263 48.1312210467 61.2026244197 78.4949927037 84.1855737234 77.133833838 90.2822623174 55.714769769 80.7094031187 80.8811339083
83.2324596557 68.6251380101 62.3938532952 75.0342926038 60.7973899604 82.5871185951 74.1769483283 72.5468427844 81.7599786386 79.6563719631
81.3292055681 91.7572808247 62.5072490947 75.4905770008 83.2481211545 71.6763745003 72.430172804 60.4972567088 61.2479445407 61.3735366641
73.5071464077 64.9265959508 68.2278434396 73.8380706024 55.3691799722 63.5795569905 63.7419972917 66.7835476632 76.9723348639 80.4474686446
60.4170392761 70.6961938703 77.4271185945 68.4269682096 82.5749222712 70.5594422469 71.8866314854 79.3328283179 75.8929192669 73.9114941097
56.787473295 63.3275678409 78.6432176027 82.0725264929 55.9401425561 79.4059789767 61.6119243203 68.0489913065 71.7911481842 75.8600273911
83.7404488265 73.7517413653 65.6849508231 93.958949219 92.2051887754 73.2318014342 55.5870767129 60.5480065132 67.4517534206 62.9709140411
77.111705832 78.4058940552 69.5190303303 74.9150169212 60.0247105466 71.6203587216 48.4981475892 75.598938747 69.0490353007 66.1969917927
69.2953901306 63.4297768555 55.304160196 52.7516360306 77.6189855968 71.8379689714 72.4880439519 90.1803807209 56.0540567675 65.2452146822
71.6653514245 77.4352494772 81.4776896731 82.8318363345 50.0164944241 80.0751669884 56.6864648134 63.9363472145 74.438773663 74.3488837542
59.8879862081 75.7692643673 68.0819241096 87.3842574946 83.2894849735 72.4347566573 73.514554242 59.0519786782 81.7204156191 73.0980511433
83.269485185 48.111248543 82.1458408608 59.8925700614 58.7285441724 63.3621104497 83.1657482194 86.6918500832 61.0448088991 69.2473415255
62.7352412265 68.6823952491 65.2946411718 62.1335831964 75.3500464269 71.4476456777 70.4595388014 81.5758332463 74.6302859624 76.1161365516
98.5420385404 70.6971215549 89.7715992322 92.4597017728 79.5833713709 79.5979551184 71.4494737621 61.6785266174 59.5438697927 77.8061050368
66.6125126371 82.2670946944 63.0620317678 78.9829548011 70.7146657077 74.7866008168 78.0925958678 79.1686554293 73.6497506294 102.4022978526
65.8331347948 79.8725224739 53.0672125022 71.8434805093 78.5897802415 46.1536157671 60.4987028054 63.0171482043 81.0035337053 76.5344404498
93.1789847526 65.3920753392 80.2498445408 78.5066842581 63.094705365 82.6169682113 63.6522028798 42.0316402595 64.0521713648 64.8664328763
65.3835078991 68.1418961902 58.5683003009 60.66183887 75.1158742786 77.3905296227 82.9998291009 71.1423283063 63.0341466602 68.1235334922
74.0240713638 95.5457264353 76.1882640289 90.2500662049 85.2258628582 53.8196192791 75.0049204724 82.4670789369 75.1044828575 86.2977205542
80.7118041847 65.756546246 73.6794092517 71.3106757756 67.8585431159 58.5218342165 86.5109243022 90.2267649507 88.0891340784 87.965943021
81.8754208011 52.6411324244 66.9796165311 67.7404406814 98.3137189904 73.5201067072 71.2021503203 73.8213586372 57.402882885 68.3270511216
63.2019484327 90.5839235201 83.7686340673 59.78981535 70.8410900187 68.557266968 77.771044016 62.9221151029 83.8985099107 61.6239296504
66.7381184029 70.0903612595 78.8896679295 58.4421624807 71.4779591361 56.9621781323 66.7926335153 70.236198735 47.3901647637 63.0426322458
65.1611637294 52.0880141265 73.1164956959 71.3391884345 77.8432806327 78.6656866693 91.9156420422 38.5038194507 87.1982021634 70.8816625773
66.895333657 73.7239108274 63.3442661637 55.6801180209 75.6902747524 44.5479574408 74.8101749194 87.8532020578 67.066655174 80.2335827756
67.0886194711 77.8484511101 52.9968176123 49.510633471 70.4308351486 88.5591700352 76.174607966 79.848648238 61.8908572504 64.1388553048
48.8913767184 79.9101482697 70.3660063663 70.1544942784 78.1218588598 59.9580536799 80.6605086835 68.6814402796 68.0644890962 80.0958898252
70.8263289197 85.490252968 64.8225724943 87.3967812366 82.0269062386 68.551523509 70.7257433531 61.0169237915 68.1631647238 78.6357279138
70.0950269673 55.7377981748 51.9187389726 78.6635584517 80.6343152361 93.5002364712 66.1049873087 84.6336999529 77.9769627114 75.5739867599
73.3038061297 56.5023194212 74.6208726922 78.3245306592 41.0432741772 71.9270130502 64.4255916994 67.5885596137 49.3818490212 64.9211389826
85.5231312015 60.5393299337 65.1157617539 77.4474594435 71.8912153387 93.3154089579 72.3465856935 66.254712874 60.4082808421 70.568691808
77.739120752 69.5087166604 67.6993633532 66.3461716612 89.8046684596 74.8233807825 78.9145789894 77.9790500018 61.5530436334 73.2050350051
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65
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75
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100
105

_996826296.xls

Chart4

45 45
50 50
55 55
60 60
65 65
70 70
75 75
80 80
85 85
90 90
95 95
100 100
105 105
110 110
72,12
70,10
Temperature
probability measure
Global Warming: Mean and STDEV by 2 Degrees
0.0122244334
0.0062096799
0.021152015
0.0165403822
0.0449138037
0.0440571668
0.0803650076
0.091848031
0.1211791574
0.1498822729
0.1539817456
0.1914624671
0.164890111
0.1914624676
0.1488012589
0.1498822729
0.1131621843
0.091848031
0.0725230542
0.0440571668
0.0391671507
0.0165403822
0.0178247713
0.0048597126
0.0068354883
0.0011172938
0.0022087681
0.0002009873

Sheet4

Bin 70,10 72,10 72,12 70,10 72,10 72,12 70,10
45 4 5 12 0.004 0.005 0.012 0.004
50 15 8 27 0.015 0.008 0.027 0.015
55 50 31 41 0.050 0.031 0.041 0.050
60 92 76 79 0.092 0.076 0.079 0.092
65 160 149 125 0.160 0.149 0.125 0.160
70 175 163 157 0.175 0.163 0.157 0.175
75 170 201 147 0.170 0.201 0.147 0.170
80 155 144 156 0.155 0.144 0.156 0.155
85 101 120 114 0.101 0.120 0.114 0.101
90 57 66 69 0.057 0.066 0.069 0.057
95 16 25 42 0.016 0.025 0.042 0.016
100 4 8 18 0.004 0.008 0.018 0.004
105 1 4 10 0.001 0.004 0.010 0.001
110 0 0 3 0.000 0.000 0.003 0.000

Sheet4

45 45
50 50
55 55
60 60
65 65
70 70
75 75
80 80
85 85
90 90
95 95
100 100
105 105
110 110
&A
Page &P
70,10
72,10
temperature
probability
Global Warming By 2 Degrees
0.004
0.005
0.015
0.008
0.05
0.031
0.092
0.076
0.16
0.149
0.175
0.163
0.17
0.201
0.155
0.144
0.101
0.12
0.057
0.066
0.016
0.025
0.004
0.008
0.001
0.004
0
0

Sheet1

70,10 66.9976784087 57.2231683185 72.4425730771 82.764735402 81.9835021906 87.331331037 48.1641236041 67.6581875671 80.9502252599 59.1329935053
63.0979583951 53.0956767255 51.5308910911 60.2237050264 62.2649294604 48.8206878293 64.3207512842 65.9595243126 71.3485305317 66.3450704854
66.7300936987 66.297594862 83.4264155349 69.1471554495 68.138423507 64.8679260342 89.7221197595 78.656729733 93.7565473071 63.4509332888
86.6145582625 53.8760231796 75.3894837038 79.0219145932 89.1891558643 69.154829311 64.7620494822 76.7513838076 66.1867615639 77.5761136031
55.5581336305 61.527624843 54.7842900635 66.3712298268 69.6752080733 70.2811702871 66.7728399497 91.9450157601 52.5751729077 62.6352302282
44.224192556 84.4767000165 57.2023636271 63.4642005428 77.5771367847 74.6671175369 78.7460875875 75.9574176703 56.2815002416 58.8426145844
76.9399447966 73.2263642424 60.6016228124 67.5905211613 71.3153567124 75.5779764807 71.3871499505 60.8903873802 88.848459149 74.8719812185
70.7223889043 78.2984115579 78.6200770966 63.6346853247 60.7680830802 81.1118879431 57.9882125242 54.4110789127 77.113249012 76.3840616349
92.0568836085 84.4375462696 83.0390390041 71.1296037883 70.0195086614 74.5370143198 69.7448526301 59.4532493272 52.2519384907 78.2833139459
74.4422449719 76.1790615291 72.134731858 59.730690686 82.3819518194 66.8878682921 61.6007823231 61.7887180345 65.7100726533 65.4663849167
64.7620494822 78.4942939793 75.1320739658 63.916958374 83.0497937789 52.3906364327 75.5057171267 68.8372792359 70.4174125934 63.4594598017
64.5040599414 78.4932025857 78.0304516814 74.5641627366 76.9136831371 86.3062395586 73.0391447581 75.8899559008 88.5283624887 66.6444306665
80.3827460407 71.4350462152 81.4104068416 68.5170120453 62.2018332654 80.7599362309 64.1817804938 75.3391204347 75.4577185438 66.8356291902
65.5923385642 56.3400717004 89.929575501 64.3351213005 70.8612914826 67.6573917593 98.3536792267 82.5197857415 78.8090700956 83.3216417453
71.8787090994 75.4195766097 67.5038008415 57.789124134 82.6668510347 67.111126504 56.9412476983 77.6425408224 77.8428229244 74.2815486267
74.0388158595 63.5190317046 77.2309831012 75.2528775996 80.7503865365 42.3055225331 74.6381501306 84.6713773574 52.7741703484 70.4549406185
83.5403297463 86.8820406543 72.3866505217 71.4505076251 88.5454155144 69.5741518433 63.4310153549 79.0737557912 69.9009332896 80.3919319372
74.347043614 84.5336343849 68.787984623 60.3828211245 54.6141236048 44.349339027 71.0318785826 72.9919192457 69.8221255737 72.0049924387
72.5823283067 84.7617356561 70.8528445505 58.8326328801 56.1008745938 71.914531822 79.5108134701 54.9120740691 63.9003828331 75.2353243518
67.8323899086 66.5642018651 68.365240117 65.6032979753 61.973777469 76.4479650064 70.5882270671 82.6345184981 72.6218913263 70.571367309
72.2695417101 72.1449068299 69.9254100658 57.761657394 72.3536131266 71.4822148842 77.5242382991 62.6382315607 76.1642481342 72.1911091608
71.1434622138 78.6812406153 88.0283677764 56.9161001698 57.6574747759 75.600327313 81.9069909488 61.2179646344 48.5462023283 61.0182168605
72.0198285711 74.2907686293 60.1506498645 61.4076397545 74.6168565859 71.2158693607 64.5990111883 71.0249550542 60.584956322 61.0468204689
80.4657146949 86.2659034686 63.279334376 68.2806798471 71.1272959455 88.4480995813 75.9501189753 86.5480287251 71.770581548 85.6018359121
63.5623918645 60.3390062173 81.9397100207 79.187510841 52.7063220437 82.719942788 68.0020334078 58.6509840508 51.2099304108 61.751133166
74.7337607612 79.1770061772 69.3052142599 69.4615791366 72.1464757083 66.47968707 79.28123427 65.0572600937 93.4347680816 77.4402350947
76.1060745793 60.189098753 78.7169610197 84.472334442 62.6862983557 66.9888790474 56.603643265 83.530780052 80.451185517 71.8436821847
48.0888174428 75.0554262998 75.2625409808 82.1610582937 60.4179958321 82.0559661809 64.380868884 62.6632881397 52.7538886166 83.7460119731
60.3463276496 85.4587269208 58.3275222601 65.9096726343 56.9214889259 85.897967387 70.2880597094 73.3046262615 79.7639713204 89.4920176
69.3910819285 59.7034285823 64.3063585306 78.4756607066 78.7236912805 75.1076540331 55.139720593 56.0383013583 68.5618615028 63.7103893899
63.7243615022 78.7899024948 61.6170963843 68.8511490301 67.6786284606 85.1841504703 56.8255144975 60.6455514065 68.3264615366 59.3889935265
55.6594058656 48.3671228215 75.8082605392 66.6112341099 74.1261159822 49.5105395606 81.6770024761 50.5130755703 64.8268737171 60.2360286796
68.9950310919 71.3477688299 87.3554326466 64.9341372485 62.0537561593 62.5325028016 75.8672185332 82.8393821797 55.6465365156 79.6927578852
85.8763214131 63.3310164124 70.8313463695 61.7166860541 76.9555198934 72.3921643333 70.4664229891 59.7021325523 67.0040789776 77.2458988143
69.9032297637 80.022290553 59.860725691 77.5863226812 82.4166035675 58.3048076299 73.9650558392 52.1887740836 70.7929656931 80.0628312794
80.353937796 71.0511030268 62.3830500848 75.7847273638 74.6432546696 77.2877355706 60.5096046859 75.966558092 86.1071511684 72.3426082407
66.1472440191 72.4875248528 88.182072381 45.9917045594 70.1679154593 68.7694764059 79.8954387795 82.3605786939 86.3555796462 51.8099695403
78.039955901 73.6688334148 77.4220906754 74.8392848839 68.6460579748 86.5933215612 74.5437900553 69.6882252162 69.7938175511 69.4753579813
53.171801432 74.4321154746 71.9277877072 76.5074118538 68.310954652 78.2563929027 83.214662431 89.0230821318 56.8944541959 76.2003664425
67.8425648806 62.5799329503 77.3928958955 93.3172613662 83.4945821628 71.7970137378 65.2670918901 67.6188519213 59.0190792939 70.7484686648
67.41372676 76.3943843998 57.2594116823 75.1914980759 79.7651991382 61.3610508884 73.7146946852 75.3091525842 79.7553538581 67.7328116074
72.330807547 65.8088210406 75.1015490499 85.7693648362 68.4101918926 59.7643192526 60.7867959337 77.2977172749 85.9632691066 63.6814560897
61.6756564744 80.2279273051 72.2295239432 74.4912667363 95.9940861724 64.2071326586 62.1540620562 82.1242919704 66.9544433043 55.8368028072
81.1945155368 57.1168938625 66.0159129841 55.6143404031 59.0162825977 76.0628053689 71.2174155017 52.5084159966 90.3723175218 72.4031805879
84.2724957186 69.7303120836 67.6141339175 70.2903561835 51.4801412867 63.1008801468 83.8271389005 71.6867261365 65.6032979753 63.9500639812
58.5395709498 82.488021639 94.7058778768 79.1583615358 69.0088781487 61.4098452791 69.1525328369 67.4524598656 66.0506670504 78.7069111032
67.1621264194 73.4414824768 77.9714482126 72.406341082 53.7053110241 70.2696879164 76.5026824814 68.3768702805 53.505858836 54.0230429982
61.8730736681 72.5973577067 63.8782480058 90.6287040783 67.8308210302 78.6344925876 82.3951394926 65.4146005621 51.5519004187 60.9849748292
70.9903601494 72.70987357 78.9543163995 49.2542439536 63.1763795757 71.52863322 71.4157308215 69.2638095136 67.5920900397 84.6961156133
78.3796294348 56.6857706365 65.2585312712 67.3963213051 60.651463122 68.0113898346 71.4984607333 60.4143805907 78.4199200501 68.2581584845
77.0621126724 62.4493295111 73.1113359 57.4061813898 92.8350472753 78.281153896 58.7538024268 84.9228526425 67.2750401867 55.7865532249
65.677330844 72.7638748179 62.916264091 75.8653995438 67.6463868734 75.2801169659 50.7623680681 58.8952061156 84.860279407 72.0706011128
78.9406285042 57.7697518968 57.3228944125 67.5219452608 68.1251903591 80.1546447695 80.1571913547 67.1007582644 75.0293692766 79.5048108051
62.3102450339 62.6010673335 67.0016801853 75.0467406254 52.7842657396 81.9944843391 89.23281161 70.1304329089 57.1063664614 70.1839907782
84.7845184983 71.6378635337 82.6277200252 80.5600975076 73.6909341361 62.3983750705 65.590655999 83.392582332 74.5463366405 77.031712812
60.5706317804 48.9766661706 69.4761310518 79.9794078778 79.0334197012 65.051211954 63.2687842374 72.8697400012 59.3215772317 75.3735675465
54.0257714823 84.5424564835 86.2115611602 63.3853814582 82.7993644128 77.0043142841 79.2424670584 59.0455910645 82.6600298245 65.6630517772
82.4997086459 54.0449163457 61.0193764663 100.1573891193 65.7310251375 65.8422108648 76.7014980232 66.886253939 52.6064595254 70.4955268196
79.0047024059 78.9588866103 67.4477191245 74.4751914174 88.0987626663 74.4709622671 70.8290498954 64.5538206703 72.8370777727 69.8037765181
85.9169303515 99.0587195195 51.6722265678 71.3809653865 86.8061887962 79.6451458376 71.9566186893 81.5315287985 80.1661726148 68.931969003
62.2246388451 59.9928525338 58.455078892 44.8317350168 58.0227733229 76.6804432208 78.026222531 82.0654476632 65.5982502797 57.4027707847
51.2677742739 65.1211293592 66.2820311339 79.7111296782 63.5736695988 80.2744934338 73.0135197449 78.9703235062 81.4280283015 76.2244907895
72.79806045 68.244948074 74.0404756874 64.5963622849 78.2273800217 69.0196329236 63.0736748865 61.5724401944 87.7259153133 74.0412942326
70.6756181392 80.422172636 60.6135144556 70.5330662134 68.1353084877 75.1137476476 88.0712959263 65.833036337 84.925171854 76.0508682509
86.0486251843 90.2281626116 79.1165702543 89.8906491278 69.4722998053 70.1748048817 85.2719621838 63.2716605144 71.7146703613 58.9221044214
69.7892246029 84.0617430588 73.2666775951 70.7814605851 62.2597680779 50.7866515766 64.3880311548 53.5207745491 80.6258084998 69.9055262379
81.7468744065 81.2663883556 78.9144123194 76.0876573116 77.8095695244 72.9008333513 69.2269749782 66.5820506986 63.3977505862 68.7956925906
88.6707438843 69.9866076905 85.1551375893 62.7441422187 87.331331037 57.4751893003 74.0122586142 74.6483592087 59.2236701271 95.260305847
75.9236526795 59.6721874393 55.413342074 53.4969457879 65.5611315272 53.9817974134 57.293790582 52.1135133971 62.9741534288 66.9952796164
80.6446577774 77.3687942859 68.5023123372 68.4636247063 60.9700363787 83.1726665131 80.1264959085 64.3772877486 86.8534825207 60.3414391156
78.0420704762 84.5358626469 73.4504068935 63.1134880171 67.9450308274 77.052312867 51.4844159118 61.5407670414 73.4520326153 66.2122501529
58.0290488363 72.4993596526 77.5364368968 52.9108219274 65.6479200591 62.3779341771 74.0255372369 67.9043877829 64.914992385 71.7465026758
60.3426669334 60.6407992967 65.9935394145 89.1939761862 51.6599029145 68.5927615853 73.7146946852 72.7043142836 85.6018359121 53.1433797226
72.8521981221 59.7527004578 73.9650558392 76.9828274718 61.4705313131 67.8535242917 64.6873231238 57.2075704843 73.9708424993 74.2304577619
68.6653619999 74.8392848839 73.486161404 93.2483216678 61.3610508884 73.7688550947 48.8062268635 68.7101091392 79.8319787867 61.2516614131
66.4886342241 64.0918314678 66.3467075759 78.4625298769 68.7424985193 88.1541508937 65.5931912154 58.3426198721 76.3915649662 68.9758066476
68.3349994181 53.8647909201 61.8240291663 64.3063585306 62.120706338 56.8527993385 68.8141780705 80.9725533548 63.4158267934 68.9381194609
69.2745415511 78.8984961621 67.5542777975 94.9907316174 46.1654180475 70.0072645889 62.7560793367 68.760233666 83.2183231472 73.6099891076
66.8999077282 57.4567265579 65.8004764267 62.2680217423 82.0370032164 64.5013996694 65.7276713758 70.3370359991 64.231529854 81.0412429422
70.9081304597 69.9858459887 69.1955178302 58.6291107032 70.7998778528 68.2340796123 58.2896418057 63.0736748865 76.1929540607 80.520102478
76.9097950472 74.9375557865 60.0256170804 81.066595107 57.0340161578 76.6594338932 55.2108885534 81.1830786409 84.8096660268 72.5831127459
78.8180968305 73.0623937164 55.079466569 52.9469743418 79.3095195552 80.8752828964 72.7003579817 65.6100509735 61.2539124125 64.4425780996
58.43868525 62.3850964478 73.5912080421 60.4131527728 88.5028511623 76.5595031629 67.7994775691 66.4804942465 64.7383457766 74.4143916966
82.5600763567 53.8168150745 52.8545696801 65.0113988234 68.164093995 86.1492607731 67.549548425 71.8538003133 61.1366785454 62.8926513348
57.0870169616 83.0229409478 71.7791307982 57.9186816543 89.6848304768 53.5266862647 86.3877302839 55.5494479561 59.8811665844 63.5868345347
63.0249714453 81.3068836072 66.6824361763 82.8796045828 61.0308133622 65.1942299958 73.5822381506 51.6681338416 75.4346401157 77.1319846029
87.6600224222 94.3348040385 65.7268300932 70.8996835277 59.4519078225 69.6729115992 48.097184794 56.4577603148 69.407168616 63.442406776
63.6487256491 60.1531282376 65.7167801767 78.9611830845 54.2703346076 76.8622966864 68.7949195202 65.3064161673 66.6977952681 58.9840637479
86.5480287251 55.9792751522 76.5974859353 76.5320136855 79.0334197012 77.0807800512 79.7565816759 61.3388137429 89.0605533135 77.8261791714
64.7804667499 62.113407643 72.4819996725 91.9195499085 89.2181687453 77.8376160673 81.2996303869 53.5207745491 74.9955360737 62.4980784272
76.8593863034 76.2598019213 75.9885110204 72.4528162612 48.6818079883 68.7771843735 60.7081701167 55.9588115214 58.7148533162 61.8240291663
64.0699581202 76.0867250795 61.2393150225 68.5989461493 91.6648004425 64.6661660033 71.0434177966 79.127006706 78.0040763351 69.0642095327
62.6742930256 68.4063151715 57.9898041399 62.0705249679 91.0164216696 72.077638328 63.689857547 74.7457433539 78.6767840912 69.4945142134
63.5755568004 61.8325784165 86.7498910741 57.4382410781 70.9511609278 83.1399247039 64.891481947 72.1370851755 80.8504536911 70.9642235455
84.1485998029 62.34310053 67.1350462147 85.9169303515 80.5400886241 74.2053784455 64.1445821605 79.5084033092 82.9837417262 63.3013668851
77.431162885 61.2404518909 69.2653329173 56.8419081395 57.1344243729 59.9358954281 60.3731122686 81.2707084554 61.3766032478 70.657973942
65.4782424538 83.8052655529 71.3709268387 77.7041477198 55.5167516216 73.0223304748 61.3566171017 80.7245341496 59.1729430601 73.6582036955
55.8012415643 69.5060079527 49.8946191731 51.3423528394 86.828198568 64.1282339933 75.3206122175 75.3444182413 89.9351234187 71.0888015822
71.02265858 67.1382294461 52.8877207619 80.3460934042 70.4855792213 70.2880597094 62.7848875814 66.139013092 69.7540271579 56.814600561
64.178142515 48.0804500915 71.9535036699 59.8132955423 68.4504597705 72.5420035854 67.3749481796 74.8306787903 75.7531110542 73.3434389479
max 100.1573891193 45
min 42.3055225331 50
average 70.2506411761 55
60
65
70
75
80
85
90
95
100
105

Sheet5

Bin 72,10
45 5
50 8
55 31
60 76
65 149
70 163
75 201
80 144
85 120
90 66
95 25
100 8
105 4
More 0

2degrees

70,10 72,10 70,10 70,10 72,10 72,12
45 0.0062096799 0.0034670231 0.0122244334 0.0062096799 0.0034670231 0.0122244334
50 0.022750062 0.0139033989 0.0333764484 0.0165403822 0.0104363759 0.021152015
55 0.0668072288 0.0445654318 0.0782902521 0.0440571668 0.0306620329 0.0449138037
60 0.1586552598 0.1150697317 0.1586552598 0.091848031 0.0705042999 0.0803650076
65 0.3085375326 0.2419635785 0.2798344171 0.1498822729 0.1268938468 0.1211791574
70 0.4999999998 0.4207403128 0.4338161627 0.1914624671 0.1787767343 0.1539817456
75 0.6914624674 0.6179113575 0.5987062738 0.1914624676 0.1971710446 0.164890111
80 0.8413447402 0.7881446661 0.7475075327 0.1498822729 0.1702333086 0.1488012589
85 0.9331927712 0.9031994505 0.860669717 0.091848031 0.1150547844 0.1131621843
90 0.977249938 0.9640697345 0.9331927712 0.0440571668 0.060870284 0.0725230542
95 0.9937903201 0.9892759189 0.9723599219 0.0165403822 0.0252061845 0.0391671507
100 0.9986500328 0.9974448094 0.9901846931 0.0048597126 0.0081688904 0.0178247713
105 0.9997673266 0.9995165175 0.9970201814 0.0011172938 0.0020717081 0.0068354883
110 0.999968314 0.9999276276 0.9992289495 0.0002009873 0.0004111101 0.0022087681

2degrees

&A
Page &P
70,10
72,10
temperature
probability
Global Warming by 2 Degrees

stdev2

70,10 72,10 70,10 70,10 72,10 72,12 70,10
45 0.0062096799 0.0034670231 0.0122244334 0.0062096799 0.0034670231 0.0122244334 0.0062096799
50 0.022750062 0.0139033989 0.0333764484 0.0165403822 0.0104363759 0.021152015 0.0165403822
55 0.0668072288 0.0445654318 0.0782902521 0.0440571668 0.0306620329 0.0449138037 0.0440571668
60 0.1586552598 0.1150697317 0.1586552598 0.091848031 0.0705042999 0.0803650076 0.091848031
65 0.3085375326 0.2419635785 0.2798344171 0.1498822729 0.1268938468 0.1211791574 0.1498822729
70 0.4999999998 0.4207403128 0.4338161627 0.1914624671 0.1787767343 0.1539817456 0.1914624671
75 0.6914624674 0.6179113575 0.5987062738 0.1914624676 0.1971710446 0.164890111 0.1914624676
80 0.8413447402 0.7881446661 0.7475075327 0.1498822729 0.1702333086 0.1488012589 0.1498822729
85 0.9331927712 0.9031994505 0.860669717 0.091848031 0.1150547844 0.1131621843 0.091848031 Weather Days with 50 degrees or less Days with 90 degrees or more
90 0.977249938 0.9640697345 0.9331927712 0.0440571668 0.060870284 0.0725230542 0.0440571668 70,10 2.3% 6.7%
95 0.9937903201 0.9892759189 0.9723599219 0.0165403822 0.0252061845 0.0391671507 0.0165403822 72,10 1.4% 9.7%
100 0.9986500328 0.9974448094 0.9901846931 0.0048597126 0.0081688904 0.0178247713 0.0048597126 72,12 3.3% 13.9%
105 0.9997673266 0.9995165175 0.9970201814 0.0011172938 0.0020717081 0.0068354883 0.0011172938
110 0.999968314 0.9999276276 0.9992289495 0.0002009873 0.0004111101 0.0022087681 0.0002009873

stdev2

&A
Page &P
72,12
70,10
Temperature
probability measure
Global Warming: Mean and STDEV by 2 Degrees

Sheet3

72,12 59.6081801631 71.0788228388 98.8808071269 77.0966445997 71.5330881575 66.9836274027 79.5990737969 70.8908712112 75.5011225918 68.0101922625
67.9480646794 69.2152818373 62.405231074 70.1619293976 56.7422623134 82.2551848613 93.3376733882 61.6132612776 68.342439772 77.4372958402
63.4889031061 77.0504650062 60.0065661273 72.383324732 103.2470365316 62.3419029579 61.3299900577 53.3025715412 72.987479325 84.2905657918
61.0489834797 69.4542834025 65.8478003969 70.5400290825 65.4954439595 63.9777110335 69.1114493746 88.790600057 81.8586951935 69.0499902702
88.1820935318 81.0266439656 67.4320128381 76.0354279918 78.9623001764 64.873008523 84.0875938592 83.7998479254 51.2557719047 73.6099147615
55.2629873708 71.7792110662 62.8547488303 81.6377971204 68.2037236401 74.7988517104 46.8467598693 113.127204895 66.5769468468 86.7190803546
41.2192068323 69.8846199156 80.4710154624 78.6592747316 64.9276873445 56.5591810299 62.8694553596 57.4604266147 54.9034550203 72.8420238373
88.7979123944 77.9364720073 72.610252755 61.0239087108 72.3539389581 81.345358194 55.1702189113 76.5127626436 78.2193066697 68.7033636494
95.5144034377 56.9702271604 91.9083297048 74.1909454517 57.8118280827 55.7859832041 67.3212773107 74.4031805879 81.939976735 55.6685492483
85.9472740557 73.85479621 78.7881546784 48.2167863082 59.2764510656 54.7139072295 74.5156759875 58.4299934416 85.7915321829 61.9261638348
86.7894206748 63.7105651548 57.9220315557 73.3924818631 48.0845093988 56.2211764189 74.4088012651 88.3919139595 68.3684012982 73.336125024
89.9804374056 88.5949404618 77.0464541346 68.7757639752 75.1766785469 66.4076444081 92.5030301004 78.9742645792 84.4797588796 68.9657073962
82.1826208265 65.9126155368 74.7140231396 55.2944740774 86.4481964526 61.9339945841 85.3547018777 60.1479288888 72.3612785804 88.4457742358
68.2769970807 68.1718549457 72.5395031621 65.9241024549 90.4750570043 75.0968840292 81.3640210252 77.568836059 66.3205102682 99.5153433904
98.9604788627 57.9165473026 67.2627786115 64.5573365545 81.6276744443 75.7095242078 77.8195291786 52.2463207743 52.000211508 104.9854083247
61.431830727 68.5534470903 65.2957052806 59.4458899285 63.5395846983 67.8858006721 48.8206544104 77.9458034229 100.601498343 49.376392053
58.9396742724 71.567071427 87.0458981807 69.0045610098 88.0913987202 56.9722189538 70.312241587 86.8425442603 90.8440571947 80.1709640654
72.6433492672 85.7773167808 73.4396300685 77.6558747019 64.5662450551 78.5183758124 82.8290805656 76.4566513679 85.7312872539 96.4760303758
98.4787377091 68.7110034049 61.9353042565 64.9440582491 65.3417893772 80.4310158854 76.3035834096 63.2822204351 89.3276748683 68.2095080264
57.4297857382 59.2554963076 66.2670592645 72.8282177077 75.6008623283 92.0330214284 65.7418124318 61.4925804256 63.5583975962 84.8628926177
69.7754396241 81.6403346106 45.9829218015 67.1822883304 100.0789390672 77.9655440054 73.734115358 87.4955796461 100.7446891889 96.2313399212
85.8271389005 63.2929706625 76.4950411393 72.9524865163 64.0521713648 62.6856919552 75.7152949517 90.8850935956 75.9665201257 69.344325493
76.6886270866 65.7260417937 67.5757903081 68.2143374432 77.6990120356 68.4135440678 80.8956221589 75.2366097003 62.1464616414 64.5673500911
70.8752097124 67.3202950564 90.9295678865 88.950925783 76.8127321861 54.9413536645 72.7730068319 80.7548596639 75.2689968066 89.4959677679
67.0726441966 81.7548490885 69.9023277774 84.2163510241 61.125326465 61.8699024925 63.8371395324 80.4627754404 86.1752389027 59.9230745137
55.2191679161 73.0519670468 73.7090678739 76.979347068 68.3462869346 39.6833976991 76.7511093726 52.1279045641 75.3071137295 84.3153949971
69.5940090735 61.8318401392 81.0510366135 75.5586253944 96.1473026108 90.1977338798 66.7704372971 76.9943537306 76.4674834498 77.8515479395
67.066655174 64.4580606603 77.328674888 88.2461037689 66.055233401 80.1640337157 49.8270284878 66.8782260617 75.4934555515 84.8612828121
70.3937959769 72.5725723895 87.2536449605 59.0651299716 64.7058615867 82.573585314 68.1332059684 78.6410757427 69.8510459187 61.0670733294
69.511526999 54.0364791958 47.9629281471 29.7272683382 68.1254707159 66.5036461213 82.143221516 64.8379338598 93.1963924812 74.660381142
57.9911986277 68.4000926411 62.3786556388 82.1222394733 74.2133463062 83.0586552182 66.254712874 81.9567841971 88.3686127053 50.0849248054
66.2227759675 85.9563053381 71.3235542206 82.0842862594 46.1909414297 77.4403381 78.6528491516 64.2951838016 52.9192195244 74.5973804441
98.8583244178 55.9176325622 72.4862022251 73.8798846213 68.0373543217 84.2998699226 98.6166898655 73.0704115994 70.8567651599 51.1318987263
71.8719385985 64.1092512523 43.4766454417 90.6881516129 62.1297223914 83.3453370432 69.4580350681 76.9263599067 65.0594049147 79.3638238973
83.2566613097 73.4784700397 84.1013181342 74.6669567887 88.4059383678 69.7913194016 68.9571808833 71.6883116182 54.0477205503 77.4749489209
77.5616874306 58.3039920456 55.9289012016 79.8247740021 63.9972196949 73.0870007827 56.9258892937 54.2886456968 85.7224742502 79.1994054451
81.7740303318 99.3033947451 88.5782148542 94.4574978347 76.3643331082 75.2309071685 83.9135165733 51.7872260388 67.4389295453 62.7463734417
54.3862708581 62.2897889115 52.1783815201 65.3053641143 62.8915287961 60.3201508055 71.3584788172 71.5560483512 52.0112345838 84.0830100059
82.913472579 86.0834526974 48.2233346701 63.3775536697 64.9963632894 80.5737838162 42.3140929341 56.5065212867 59.3246633797 59.8098151385
83.1827466753 80.9913646661 69.0953922457 72.9082850738 63.3823285169 90.7314799405 76.2273086365 81.2734080681 60.1613803154 73.8455057216
66.1680835036 92.491243049 74.4369046514 81.939976735 59.3438991926 82.8470067062 45.1752905063 61.5369455771 77.4189877119 78.8140207077
99.2064789897 87.328050722 79.0199530455 84.4734560814 69.1312990965 62.8338759269 86.06154297 69.8482492224 61.4845041126 64.4591793388
78.146974556 79.8964512795 60.0864834267 93.4728424908 78.0175352701 79.5195930549 71.9903684511 65.2516675472 86.9516563397 47.1835639472
80.1628604676 86.399029169 45.9152553957 95.3965329244 79.5979551184 93.0580037674 92.7811717701 84.7219391288 65.599399204 76.8107403927
81.4776896731 72.3823970474 65.0376998236 79.3129103839 82.646872397 79.1313843364 77.2366294767 82.135336197 102.0517422147 77.529000191
63.7629247648 92.7156881515 63.4900763542 76.2595593186 79.5263051258 98.9262091024 83.4592239697 66.6064144751 81.3416201707 49.7198536322
74.6895486371 50.5225736559 78.9883981269 90.2326039067 91.9119858735 50.8471541251 71.9398642103 54.8704676474 75.3901551433 65.0474677967
78.1155833464 92.0145223062 85.9364692586 89.8600566869 46.4976230431 66.0063935355 69.3734793457 81.6936764749 61.4453503657 56.0983400645
72.2758770279 56.6594801056 76.5571277951 41.5287260693 73.2170403352 81.7612473837 89.8212576429 91.0872742678 81.079112715 77.8567184169
61.4453503657 56.9521100259 61.1557490628 78.3551306084 78.5652511694 50.67122147 68.9552845869 74.1191044652 84.6401118905 69.790391717
72.2997512638 58.3408811507 67.5767725623 86.2455792229 81.9866065284 77.6435692386 66.3297461868 72.6580557965 58.1478681851 71.935280357
85.8324867294 75.8320058593 56.1005228518 91.3251980818 87.4282133735 59.1793988859 76.4871558202 66.262952896 77.1217739383 66.9535458654
64.4625353742 84.6433042169 85.0040098156 67.1414702082 69.5255923346 51.0100991959 86.6491765918 89.0259045262 69.5133960106 76.4340322347
83.2225006887 61.8449641478 67.0926030579 74.5522786018 93.2888335227 76.7292814997 60.7219473749 58.2545791984 67.0156598061 59.9474398767
83.3109308586 70.4919259077 60.3230975684 66.8127970129 61.5785003901 57.8578848944 73.233643161 44.1157655586 86.2585940921 71.379624569
68.437527443 54.8679028724 82.8857511805 72.6130221664 93.680862119 71.6322958395 66.2886552162 63.2762450549 94.1276241064 79.1851081884
84.171740309 101.9888779409 70.9083880791 71.5790221874 54.5780832907 105.276155591 79.1456270234 86.0051452036 69.4420734361 65.3128674456
64.4121402728 88.198027879 77.78752406 69.172840267 49.2225055494 73.6664216673 50.8340574014 61.0308663453 58.8296072236 59.8082871874
84.9414456751 78.4779942477 53.6500712768 71.3906612872 79.5006028055 50.4493411426 78.3456354837 61.3979565968 61.1640436545 75.6787196223
60.9651917329 100.3559347736 65.7334087008 43.0403062636 84.5906444737 65.3268099994 92.3699892154 85.443732314 68.5352617437 74.3498250812
78.7773908086 84.2781511891 65.9907866064 68.5008009895 59.2102307563 65.1719412416 94.1427399083 50.8297463965 76.3820000428 67.2598045638
65.1989259494 49.4946991238 70.9922480381 74.2535095923 62.4796095507 64.6139935269 56.2603301659 69.2011482896 65.8195196592 118.1004674435
75.1073341233 78.1166338128 65.3674916974 77.222495929 61.354491845 79.4182025855 57.1020402275 72.4347566573 72.5266247172 84.810833141
62.8608879196 60.8738148002 51.0396759636 58.7538917897 79.0058058554 55.694006005 89.4535671249 59.8635389905 45.489830154 90.299833755
81.9141107057 71.7250370143 75.6258279579 104.1140396409 85.7844108394 83.1388999358 85.8396080729 74.2376298148 80.5832652985 65.6131507638
49.892402967 68.4356175042 70.1934979587 57.1277971175 75.026707418 57.4776433494 77.8794739743 85.3308549266 68.0925651976 95.4894105233
74.1778760129 81.1526180768 51.048188834 72.258428372 59.4712648307 59.1972704568 81.196874089 69.9219046509 51.489002726 63.8845060165
79.3882165452 82.3813908936 54.4480164534 59.2069838602 81.991817933 66.3338525554 73.0934536476 67.2081543597 75.6681467463 89.6759931492
68.3876098263 48.1312210467 61.2026244197 78.4949927037 84.1855737234 77.133833838 90.2822623174 55.714769769 80.7094031187 80.8811339083
83.2324596557 68.6251380101 62.3938532952 75.0342926038 60.7973899604 82.5871185951 74.1769483283 72.5468427844 81.7599786386 79.6563719631
81.3292055681 91.7572808247 62.5072490947 75.4905770008 83.2481211545 71.6763745003 72.430172804 60.4972567088 61.2479445407 61.3735366641
73.5071464077 64.9265959508 68.2278434396 73.8380706024 55.3691799722 63.5795569905 63.7419972917 66.7835476632 76.9723348639 80.4474686446
60.4170392761 70.6961938703 77.4271185945 68.4269682096 82.5749222712 70.5594422469 71.8866314854 79.3328283179 75.8929192669 73.9114941097
56.787473295 63.3275678409 78.6432176027 82.0725264929 55.9401425561 79.4059789767 61.6119243203 68.0489913065 71.7911481842 75.8600273911
83.7404488265 73.7517413653 65.6849508231 93.958949219 92.2051887754 73.2318014342 55.5870767129 60.5480065132 67.4517534206 62.9709140411
77.111705832 78.4058940552 69.5190303303 74.9150169212 60.0247105466 71.6203587216 48.4981475892 75.598938747 69.0490353007 66.1969917927
69.2953901306 63.4297768555 55.304160196 52.7516360306 77.6189855968 71.8379689714 72.4880439519 90.1803807209 56.0540567675 65.2452146822
71.6653514245 77.4352494772 81.4776896731 82.8318363345 50.0164944241 80.0751669884 56.6864648134 63.9363472145 74.438773663 74.3488837542
59.8879862081 75.7692643673 68.0819241096 87.3842574946 83.2894849735 72.4347566573 73.514554242 59.0519786782 81.7204156191 73.0980511433
83.269485185 48.111248543 82.1458408608 59.8925700614 58.7285441724 63.3621104497 83.1657482194 86.6918500832 61.0448088991 69.2473415255
62.7352412265 68.6823952491 65.2946411718 62.1335831964 75.3500464269 71.4476456777 70.4595388014 81.5758332463 74.6302859624 76.1161365516
98.5420385404 70.6971215549 89.7715992322 92.4597017728 79.5833713709 79.5979551184 71.4494737621 61.6785266174 59.5438697927 77.8061050368
66.6125126371 82.2670946944 63.0620317678 78.9829548011 70.7146657077 74.7866008168 78.0925958678 79.1686554293 73.6497506294 102.4022978526
65.8331347948 79.8725224739 53.0672125022 71.8434805093 78.5897802415 46.1536157671 60.4987028054 63.0171482043 81.0035337053 76.5344404498
93.1789847526 65.3920753392 80.2498445408 78.5066842581 63.094705365 82.6169682113 63.6522028798 42.0316402595 64.0521713648 64.8664328763
65.3835078991 68.1418961902 58.5683003009 60.66183887 75.1158742786 77.3905296227 82.9998291009 71.1423283063 63.0341466602 68.1235334922
74.0240713638 95.5457264353 76.1882640289 90.2500662049 85.2258628582 53.8196192791 75.0049204724 82.4670789369 75.1044828575 86.2977205542
80.7118041847 65.756546246 73.6794092517 71.3106757756 67.8585431159 58.5218342165 86.5109243022 90.2267649507 88.0891340784 87.965943021
81.8754208011 52.6411324244 66.9796165311 67.7404406814 98.3137189904 73.5201067072 71.2021503203 73.8213586372 57.402882885 68.3270511216
63.2019484327 90.5839235201 83.7686340673 59.78981535 70.8410900187 68.557266968 77.771044016 62.9221151029 83.8985099107 61.6239296504
66.7381184029 70.0903612595 78.8896679295 58.4421624807 71.4779591361 56.9621781323 66.7926335153 70.236198735 47.3901647637 63.0426322458
65.1611637294 52.0880141265 73.1164956959 71.3391884345 77.8432806327 78.6656866693 91.9156420422 38.5038194507 87.1982021634 70.8816625773
66.895333657 73.7239108274 63.3442661637 55.6801180209 75.6902747524 44.5479574408 74.8101749194 87.8532020578 67.066655174 80.2335827756
67.0886194711 77.8484511101 52.9968176123 49.510633471 70.4308351486 88.5591700352 76.174607966 79.848648238 61.8908572504 64.1388553048
48.8913767184 79.9101482697 70.3660063663 70.1544942784 78.1218588598 59.9580536799 80.6605086835 68.6814402796 68.0644890962 80.0958898252
70.8263289197 85.490252968 64.8225724943 87.3967812366 82.0269062386 68.551523509 70.7257433531 61.0169237915 68.1631647238 78.6357279138
70.0950269673 55.7377981748 51.9187389726 78.6635584517 80.6343152361 93.5002364712 66.1049873087 84.6336999529 77.9769627114 75.5739867599
73.3038061297 56.5023194212 74.6208726922 78.3245306592 41.0432741772 71.9270130502 64.4255916994 67.5885596137 49.3818490212 64.9211389826
85.5231312015 60.5393299337 65.1157617539 77.4474594435 71.8912153387 93.3154089579 72.3465856935 66.254712874 60.4082808421 70.568691808
77.739120752 69.5087166604 67.6993633532 66.3461716612 89.8046684596 74.8233807825 78.9145789894 77.9790500018 61.5530436334 73.2050350051
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85
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105