One of the main goals of statistical hypothesis testing is to estimate the PP value, which
is the probability of obtaining the observed results, or something more extreme, if the null
hypothesis were true. If the observed results are unlikely under the null hypothesis, reject
the null hypothesis. Hypothesis testing is used to assess the plausibility of a hypothesis
by using sample data. The test provides evidence concerning the plausibility of the
hypothesis, given the data. Statistical analysts test a hypothesis by measuring and
examining a random sample of the population being analysed. The one-tailed test refers
to a test of null hypothesis, in which the alternative hypothesis is articulated directionally.
Here, the critical region lies only on one tail. However, if the alternative hypothesis is not
exhibited directionally, then it is known as the two-tailed test of the null hypothesis.,
wherein the critical region is one both the tails. Hypothesis testing is a way of claiming
some aspect of a population. Testing a hypothesis allows you to test the claim about the
population and find out how likely your claim is true. In a hypothesis test you are
evaluating two statements. You also evaluate the null hypothesis, alternative hypothesis,
the test statistic, the p-value, and the rejection region. A hypothesis testing should be used
whenever you want to make any claims about the distribution of data or whether one set
of results are different from another set of results in applied machine learning.
My personal and professional life is never used for hypothesis testing, however I was able
to come up with an example. My husband and I are thinking about purchasing a new car
in the next few months. The main issue we have is finding a car that could fit our family
of five comfortably with three car seats. One could argue that a hypothesis testing could
be used to determine which vehicle has more room in it based on a few findings.
The "p" stands for probability but stands for different probabilities depending on what
probability we are referring to. In a statistical hypothesis, the 'P" can stand for the
probability of a type one error, or the significance of the test. In comparison, the "alpha"
level is the significance level at which you are conducting a test.
For example, sets say I use a 95% confidence level to conduct a z test. That means, that
the significance level of my test is an alpha of .05. By this, I am allowing for a potential
.05 or less for a type one error (rejecting the null hypothesis when the null hypothesis is
true).In a two-tailed test, this means that my z score must be greater than 1.96. A greater
z score puts by z "further out in the tails" of the normal distribution. Since the "tails"
correspond to my type one error, then a score greater than 1.96 will be "statistically
significant", where I risk less than a .05% chance of committing a type one error.
Hypothesis testing is important tool in statistics to be able to draw conclusions about the
population by using a sample data. Depending on the situation you might need a one or
two tailed test. A two-tailed test allows for the possibility that the test statistic is either
very large or very small with the negative being the small. A one-tailed test allows for
only one of these possibilities .The one-tailed test draws results in a one direction. While
the two-tailed gives two possibility results and that is positive and negative results. I think
the easiest way to understand is when relating to the medical field. A real life scenario
of hypothesis testing is used in clinical trials to determine the outcome of the new
treatment or medication. Let’s say that there is a company looking to prove that their
medication reduces high blood pressure. To do this they might measure the blood pressure
of the patients before and after the trail to compare results. They would then run a
hypothesis test on differences in the null and alternative hypothesis. Hypothesis testing
can relate to my personal and professional life at work. However, I most easily can relate
this to a medication issue I had while I first became pregnant. I was extremely sick
starting at 4 weeks along and I found out early due to this. By the time I hit the 7-week
mark, I had lost several pounds due to not being able to eat absolutely anything and keep
anything down. The doctors first had me switch prenatal vitamins due to the iron in them
but after testing several with different formulas and flavours, I was still very much sick.
So, then they prescribed me a specific prenatal along with a combination medicine
specifically formulated for pregnant women and I was to see how I would react to that.
When given that medicine, within two days I was getting sick much less and actually
beginning to sleep with it as well. After much trial and error, I found a medicine
combination that allowed me to eat finally at about 11 weeks of pregnancy and become
much healthier for my son who is almost 11 months old now! I had to evaluate the
different vitamin levels in my body along with my diet and what my body was willing to
withstand to allow me a safe and healthy pregnancy . I decided to write about hypothesis
testing in business for this week's post. Hypothesis testing can benefit any organization
by helping make data-driven decisions. This means that by identifying new opportunities
to pursue and backing the decisions with data, it can really empower a business to
become more profitable.So, what is hypothesis testing? Hypothesis testing is figuring out
why something has happened or might happen under certain conditions. For example, if
an organization wants to launch a new marketing campaign during a slow period. Doing
so can be expensive depending on the campaign's size. Therefore, the company may wish
to test the campaign on a smaller scale to understand how it will perform. Pending the
final results, the business would then know whether it makes sense to launch it
broadly.Hypothesis testing is a method used to determine a possible conclusion from two
different hypotheses. One tailed tests are used to determine if there is a relationship
between two variables in only one direction while two tailed tests test for either direction.
An example of hypothesis test is the testing of the COVID vaccine before it was released
to the public. There must have been several theories on how the vaccine will work, how
much each shot will need to have in it to be effective. As the testing continued with
several age groups it allowed scientist to determine the information needed to provide to
determine if the vaccine is effective or not. With so much being focused on vaccines
these days this is the first thing that came to mind that pretty much effects everyone's
personal life. Hypothesis testing is used to assess the plausibility of a hypothesis by using
sample data. The test provides evidence concerning the plausibility of the hypothesis,
given the data. Statistical analysts test a hypothesis by measuring and examining a random
sample of the population being analyzed. Life is an educated guess, the only fair thing I
can think of in my personal life is taking a gambling with pharmaceutical companies,
science, the stock market, technology and general purchases. Why, because it is a constant
challenge of finding the answers to any values. Many took risks and guesses to get, what
we know, now. Tricky, may I say look at the COVID vaccinations, and other vaccinations
before COVID. It was all base on testing, guessing, and taking risks to save lives. Then,
the technology such as the telephone, television, computers and so forth, because of
competition, change and to create a better life, but it takes time, calculation, formulas,
and determination to make it happen.My personal life, it deals with transportation of
international express freight. It, all about calculation, time, metrics, and the values of. Not
to appear ugly but at cost, with service. Moving international freight is big business, and
it took one person to start the idea, which created jobs, and income.Getting back to
research of vaccines in America. Those, are called mad, (mad scientists, doctors, and
creators), why, so we need a better life. Now, 62% of the US population has been
vaccinated, with great results to prevent long hospitalizations and death of the COVID
vaccine. The concept of hypothesis testing is a statistical method that is used in many
types of situations. Hypothesis is a very important concept. When making a hypothesis
we are making a assumption which we make by our observations. Evaluating two
mutually exclusive statements on population data using sample data. The two mutually
exclusive statements are Null Hypothesis and Alternative Hypothesis. The difference
between a one-tailed and two-tailed test is that a one-tailed test is used ascertain if there
is any relationship between variables in a single direction for example left or right. The
two-tailed is used to identify whether or not there is any relationship between variables in
either direction. An example from my personal life using hypothesis testing would be a
doctor giving me a certain medication to see if it treats against my cramps. Another
example from my professional life would be my supervisor changing the schedule up
adding more people to the schedule to see if it helps speed up the customer service and
helping members in and out quicker. There are many ways hypothesis testing can be used
in both personal and professional life. The concept of hypothesis testing is to allow the
researcher to determine whether the data from the sample is statistically significant. It is
used to measure the validity and reliability of outcomes in any systematic investigation.
The differences between the one and two tailed hypothesis test is that the one asserts the
value of a parameter that is less or greater than the value asserted in the null hypothesis.
As for the two tailed asserts the value of a parameter that is not equal to, that is, either
less than or greater than the value asserted in the null hypothesis.An example of a
hypothesis test will be me experimenting how eating a plant base diet for 2 weeks will
improve my health versus eating meat meals. To prove this I will eat meat meals for 2
weeks and take a fasting blood test to get all the results of my cholesterol and glucose
test. Then the next 2 weeks eat a plant base meals and take a fasting blood test to see
those results. The results of the two will be different. The meat meals will have a more
of cloudy look on the top of the blood sample while the plant base blood sample will
have a clearer substance on the top. Resulting that eating plant base meals are beneficial
to your health.
Hypothesis testing is done to determine possible conclusions for two varying hypotheses.
This testing is used to assess the plausibility of a particular hypothesis by leveraging
sample data. Analyst’s test said hypothesis by assessing random samplings of the overall
population being tested/analyzed. This testing should be used when seeking to provide
evidence for making determinations related to the analyzed population; providing data to
support how reliable data can be mined from the findings of data collected. In simplest
terms, a one tailed test only has one end/outcome while a two-tailed test has two
ends/outcomes. Dependent on the data one wishes to collect should determine which
approach is taken when first beginning to gather insight(s).
In my personal life, hypothesis testing came into play when attempting to learn which
thyroid medication would best support me and my health needs and goals. My care team
started with the most prescribed medication for those who no longer have a thyroid and
kept close track of blood levels over the next few months. Upon receiving my first lab
results we determined that a medication adjustment might be in order but proceeded on
the same path for another 2 months. At the next round of labs, it was determined that the
generic medication was not an effective solution for me at that I would need to be
prescribed the name brand medication. This testing if you will be important as it lay the
groundwork that my doctor needed by which to create a prior authorization to get the
name brand medication approved for my therapy. Without this initial testing, my prior
authorization would not have been approved by insurance and I would have been
responsible for paying 100% of the medication cost which I would not have been able to
afford.
Hypothesis testing is an act to test an assumption regarding a population parameter.
Hypothesis testing is a method of statistical i French used to determine a possible
conclusion from two different and likely conflicting hypothesis. There are two types of
hypothesis testing, null and alternative. The purpose of this testing is to test whether bill
hypothesis (where there is no difference) can be rejected or approved. One tailed testing
is used to see if there is a relationship between variables in a single direction being left
or right. Two tailed testing is used to see if there is any relationship between the variables
in either direction.
Real life scenario:
A hospital reports that Covid patients are deserting at an average of 85 percent while they
do no have oxygen on. To test this hypothesis, we need to record thirty patients with
Covid without oxygen to see what they are sating at for their oxygen. We record those
thirty patients out of the Covid positive patients in the hospital ( about three hundred) .
We then calculate the mean of all of the oxygen sats and get a number. We then take the
calculated mean and compare it to the sample mean and see if it is accurate or not.
Hypothesis testing is used in two different ways, a one or two-tailed test to get the results
we are seeking for final results. The one-tailed test draws results in a one direction. While
the two-tailed gives two possibility results and that is positive and negative results. I think
how this could be used would be, well what comes to my mind would be evaluating a
pay raise in a work area and what surrounds the business. If a company is trying to stay
competitive with other businesses in the similar type of field do surveys how those other
companies are paying their employees in order to try and keep their employees in
business. What I can remember hearing in a supply chain, when business are being build
around and close by they try to compare the pay rate and what is competitive in order
for no disrubtions in rehiring new employees. For my own personal experience I would
have to say that I feel I can use a hypothesis test for when I am trying to figure out the
number of clients that will show up for the children's crisis center evaluation weekly or
for the number of therapist that will be available in-person or over video conference
weekly. This information helps me tremendously because it allows me to prepare my
weekly spreadsheets in advance for attendance and reminder calls for each client. I can
somewhat calculate how many clients will come to their therapy session in-person and
have a pattern of doing so versus the ones that will attend over video conference.
