Application of the Pearson Correlation and Chi-Square Test
The chi-square test of independence is used to determine whether two or more samples of cases differ on a nominal level variable. A Pearson correlation is used to determine the relationship between two continuous variables. Both the chi-square test of independence and correlation are widely used in the analysis of public health data. The purpose of this assignment is to practice calculating and interpreting the Pearson correlation coefficient and a chi-square test of independence. After analyzing the data, communicate the results in a PowerPoint presentation. Refer to the Using and Interpreting Statistics: A Practical Text for the Behavioral, Social, and Health Sciences textbook and instructional videos for assistance completing this assignment. Part 1 Use SPSS and the Topic 2 “Health Behavior Data Set” and complete the following: Application of the Pearson Correlation and Chi-Square Test
- Conduct a Pearson correlation to determine the relationship between age and annual income.
- Conduct a chi-square test to determine the relationship between sex and smoking status.
- Export the SPSS output for the Pearson correlation and chi-square tests.
- Explain why the statistical test is most appropriate for analyzing the data and whether the assumptions were met.
- What are the null and alternative hypotheses?
- What is the decision rule?
- What is the test statistic and p-value?
- How do you interpret the results? (What was done? What was found? What does it mean? What suggestions are there for the creation of a health promotion intervention?)