Description
Another way to think of statistical significance is the risk associated with not being 100% positive that what occurred in an experiment is a result of what you did or what was tested. Therefore, it is the degree of risk you are willing to take to feel confident that there is a difference.
The null hypothesis states that there is no difference between the two things you seek to compare. You reject the null hypothesis when you have a statistically significant finding (.05 and .01), because there is only a 5% or 1% chance that you are wrong. In other words, you are 95% or 99% confident that your results are accurate. Nevertheless, as you can see, you still have taken a 5% or 1% risk that you are incorrect.
For this Assignment, you complete the Statistical Significance and Null Hypothesis Worksheet and write a short paper.
LEARNING RESOURCES
Required Readings
Salkind, N. J., Frey, B. B. (2020c). Statistics for people who (think they) hate statistics (7th ed.). Sage.
Part IV, “Significantly Different: Using Inferential Statistics” (p. 165)
Chapter 9, “Significantly Significant: What It Means for You and Me” (pp. 166–184)
Document: Statistical Significance and Null Hypothesis Worksheet Download Statistical Significance and Null Hypothesis Worksheet
(Word document)
To prepare:
Complete the Statistical Significance and Null Hypothesis Worksheet in the Learning Resources.
Submit the completed Statistical Significance and Null Hypothesis Worksheet and a 1- to 2-page paper in which you respond to the following:
Describe the level of statistical significance.
Describe a null hypothesis.
Identify Type I and Type II errors, and explain which error you think is worse.
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Statistical Significance and Null Hypothesis Worksheet
Objective
•
Answer the following questions in complete sentences about statistical
significance and null hypothesis
Statistical Significance and Null Hypothesis
Describe how probability can identify differences between groups that are not due to
chance.
Describe why one cannot control for a Type I error.
Describe how a significant level is referred to as the level of risk you are willing to take.
Describe the null hypothesis.
Describe what happens when you make a Type I error.
Describe the three commonly reported levels for statistical significance when testing the
null hypothesis.
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