## Hypothesis Testing

Hypothesis testing allows us to use an analytical process to determine if a hypothesis is retained or rejected. This process compares a null hypothesis (HO), which states things as we believe they are, to an alternative hypothesis (HA), which proposes a change to what we believe exists.

Respond to the following in a minimum of 175 words:

a. Discuss the concepts of hypothesis testing, including what you are evaluating.

b. When hypothesis testing should be used.

c. What are the differences between a one- and a two-tailed test?

d. Describe one example from your personal or professional experiences where you could apply a hypothesis test. Discuss how knowing that information helped you.

Hypothesis testing is a statistical method used to determine whether there is enough evidence to support a claim about a population. The claim is made in the form of a hypothesis, which is a statement about the population. The hypothesis is tested using data from a sample of the population.

The null hypothesis (H0) is the statement that there is no difference between the population and the sample. The alternative hypothesis (HA) is the statement that there is a difference between the population and the sample.

The goal of hypothesis testing is to determine whether the data from the sample provide enough evidence to reject the null hypothesis. If the data do provide enough evidence to reject the null hypothesis, then we say that the alternative hypothesis is supported.

b. When hypothesis testing should be used.

Hypothesis testing should be used when we want to determine whether there is enough evidence to support a claim about a population. For example, we might want to use hypothesis testing to determine whether there is a difference in the average heights of men and women, or whether there is a difference in the average prices of houses in two different cities.

Hypothesis testing should not be used when we are simply interested in describing the data. For example, we would not use hypothesis testing to simply describe the heights of a group of people.

c. What are the differences between a one- and a two-tailed test?

A one-tailed test is used when we are only interested in determining whether the mean of the population is greater than or less than the mean of the sample. A two-tailed test is used when we are interested in determining whether the mean of the population is different from the mean of the sample, regardless of whether it is greater or less than the mean of the sample.

The choice of whether to use a one-tailed or a two-tailed test depends on the hypothesis being tested. If the hypothesis only specifies a direction (for example, that the mean is greater than a certain value), then a one-tailed test should be used. If the hypothesis does not specify a direction (for example, that the mean is different from a certain value), then a two-tailed test should be used.

d. Describe one example from your personal or professional experiences where you could apply a hypothesis test. Discuss how knowing that information helped you.

In my previous job as a marketing manager, I was responsible for developing and executing marketing campaigns. I would often use hypothesis testing to determine whether a particular marketing campaign was effective. For example, I might hypothesize that a new ad campaign would increase brand awareness. I would then collect data on brand awareness before and after the ad campaign was launched. If the data showed that brand awareness had increased, then I would have evidence to support my hypothesis. This information would help me to determine whether to continue using the ad campaign or to make changes to it.