Describe the purpose of hypothesis testing. Explain the four steps of hypothesis testing while using an
important current event in which you could study.
Hypothesis testing is used as a way for researchers to use sample data to make inferences about a
population of interest. It can be difficult or impossible to study a whole population of interest, so
collecting sample data and studying the sample allows for questions about the population to be
answered. The four steps are:
1. Statement of the hypothesis. During this step the researcher states the hypothesis and identifies the
null hypothesis as well as the alternative hypothesis.
2. Choose a significance level, locate the critical region, and set the criteria for a decision. This step is
used to determine what the critical region and use the null hypothesis to predict the sample mean. The
alpha level is selected to determine boundaries of the critical region.
3. Collect data and compute the test statistics. During this step, sample data is collected and analyzed.
The raw data for the sample is computed into a z-score. The z-score describes exactly where the sample
mean is in comparison to the hypothesized population mean in the null hypothesis.
4. Make a decision. During the final step, a researcher makes a decision about the null hypothesis using
the collected data. Based on the analysis of the sample data, the researcher decides whether to reject or
fail to reject the null hypothesis. If the sample data is unlikely to have occurred under the null
hypothesis, the null hypothesis is rejected. If the sample data is likely to have occurred under the null
hypothesis, the null hypothesis is not rejected.
A current event that hypothesis testing could be applied to is the impact of social media on mental
health. A study could be conducted to test the hypothesis that social media use is associated with
increased rates of depression and anxiety. The four steps of hypothesis testing could be:
1. State the null and alternative hypotheses. H0: there is no relationship between social media use
and depression or anxiety. H1: There is a relationship between social media use and depression
or anxiety.
2. Choose a significance level. For this example, I would choose a significance level of 0.05.
3. Collect and analyze data. Surveys could be administered to a sample of individuals in order to
collect data on social media use and levels of depression and/or anxiety. The data could then be
analyzed using a z-score to describe exactly where the sample mean is in comparison to the
hypothesized population mean.
4. Make a decision. Based on the results of the data analysis, you would decide whether to reject
or fail to reject the null hypothesis. If the sample data suggests that there is a relationship
between social media use and anxiety or depression, you would reject the null hypothesis and
conclude that social media use is associated with increased rates of depression and anxiety. If
the sample data does not support this relationship, you would fail to reject the null hypothesis
and conclude that there is no relationship between social media use and increased rates of
depression and anxiety. (Gravetter et al., 2021).
important current event in which you could study.
Hypothesis testing is used as a way for researchers to use sample data to make inferences about a
population of interest. It can be difficult or impossible to study a whole population of interest, so
collecting sample data and studying the sample allows for questions about the population to be
answered. The four steps are:
1. Statement of the hypothesis. During this step the researcher states the hypothesis and identifies the
null hypothesis as well as the alternative hypothesis.
2. Choose a significance level, locate the critical region, and set the criteria for a decision. This step is
used to determine what the critical region and use the null hypothesis to predict the sample mean. The
alpha level is selected to determine boundaries of the critical region.
3. Collect data and compute the test statistics. During this step, sample data is collected and analyzed.
The raw data for the sample is computed into a z-score. The z-score describes exactly where the sample
mean is in comparison to the hypothesized population mean in the null hypothesis.
4. Make a decision. During the final step, a researcher makes a decision about the null hypothesis using
the collected data. Based on the analysis of the sample data, the researcher decides whether to reject or
fail to reject the null hypothesis. If the sample data is unlikely to have occurred under the null
hypothesis, the null hypothesis is rejected. If the sample data is likely to have occurred under the null
hypothesis, the null hypothesis is not rejected.
A current event that hypothesis testing could be applied to is the impact of social media on mental
health. A study could be conducted to test the hypothesis that social media use is associated with
increased rates of depression and anxiety. The four steps of hypothesis testing could be:
1. State the null and alternative hypotheses. H0: there is no relationship between social media use
and depression or anxiety. H1: There is a relationship between social media use and depression
or anxiety.
2. Choose a significance level. For this example, I would choose a significance level of 0.05.
3. Collect and analyze data. Surveys could be administered to a sample of individuals in order to
collect data on social media use and levels of depression and/or anxiety. The data could then be
analyzed using a z-score to describe exactly where the sample mean is in comparison to the
hypothesized population mean.
4. Make a decision. Based on the results of the data analysis, you would decide whether to reject
or fail to reject the null hypothesis. If the sample data suggests that there is a relationship
between social media use and anxiety or depression, you would reject the null hypothesis and
conclude that social media use is associated with increased rates of depression and anxiety. If
the sample data does not support this relationship, you would fail to reject the null hypothesis
and conclude that there is no relationship between social media use and increased rates of
depression and anxiety. (Gravetter et al., 2021).
