Q: Using StatCrunch, calculate the chi-square statistic and degrees of freedom for the following set of data for 300 people:

Is the value of the chi-square statistically significant at the 0.05 level?

Q: Write a paragraph summarizing the results of the analysis in Exercise 1

Q: Using StatCrunch, calculate the chi-square statistic and degrees of freedom for the following set of data for 180 people undergoing a knee replacement treatment with a drug supplement:

Is the value of the chi-square statistically significant at the 0.05 level?

Q: Match each of the nonparametric tests in Column A with its parametric counterpart in Column B

Q: Using the information provided, indicate which statistical test you think should be used for each of the following situations:

a. Independent variable: normal birth weight vs. low birth weight infants; dependent variable: breathing rate (in breaths per minute).

b. Independent variable: time of measurement of same patient (before, during, and after surgery); dependent variable: heart rate.

c. Independent variable: time of measurement (before, during, and after intervention); dependent variable: did vs did not exercise regularly.

d. Independent variable: infertility treatment A vs infertility treatment B vs control condition; dependent variable: did vs did not become pregnant.

Q: The relationship between cigarette smoking and major depressive disorder has been studied for decades. In the doc sharing area of the course, you will find an excel spreadsheet of data from a study on smoking and depression by the St Louis Epidemiologic Catchment Area Survey of the National Institute of Mental Health. The file is labeled “Catchment Area Survey”. Using this data set in StatCrunch, calculate the chi-square statistic and degrees of freedom for the items “smoker” and a measure of depression, “FeltDown”. Construct a contingency table for this data as we did in week 1. Be sure to include and label the row, column and total %’s as well as the expected counts. Is the value of the chi-square statistically significant at the 0.05 level? Any reason to use a correction to the chi-square test here given your expected counts?