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. h 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.
