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. i 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.
