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# Week 3 Assignment

Week 3 Assignment 1. Using StatCrunch, calculate the chi-square statistic and degrees of freedom for the following set of data for 300 people: Group A Group B Group C Total Had flu shot 20 30 32 82 Didn’t have flu shot 80 70 68 218 Total 100 100 100 300 Is the value of the Read More

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- Mar 20, 2021
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Week 3 Assignment

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

Group A Group B Group C Total

Had flu shot 20 30 32 82

Didn’t have flu shot 80 70 68 218

Total 100 100 100 300

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

2. Write a paragraph summarizing the results of the analysis in Exercise 1.

3. 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:

Treatment with drug X Treatment without Drug X Total

Had > 8 wk rehab 18 32 50

Had < 8 wk rehab 70 60 130
Total 88 92 180
Is the value of the chi-square statistically significant at the 0.05 level?
4. Write a paragraph summarizing the results of the analysis in Exercise 3.
5. Given each of the following circumstances, determine whether the calculated values of chi-square are statistically significant:
a. χ2 = 3.02, df = 1, α = 0.05
b. χ2 = 8.09, df = 2, α = 0.05
c. χ2 = 10.67, df = 3, α = 0.01
d. χ2 = 9.88, df = 2, α = 0.01
6. Match each of the nonparametric tests in Column A with its parametric counterpart in Column B
A. Nonparametric Test B. Parametric Test
1. Mann-Whitney U-test a. Paired t-test
2. Friedman test b. One-way ANOVA
3. Kruskall-Wallis test c. Independent groups t-test
4. Wilcoxon signed-ranks test d. Repeated measures ANOVA
7. 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.
8. 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?
9. Write a paragraph summarizing the results of the analysis in Exercise 8. What can you conclude about smoking and depression (“Feeling Down”) in this sample?
10. Below are three (a-c) sets of cells of 2 X 2 contingency tables including the expected frequencies (Totals not included). Identify which statistical procedure would be appropriate for each, using the most conservative approach.
a.
Aspirin Taker?
Cancer
No
Yes
Yes
% within Cancer
% within Aspirin Taker
% of Total
Expected Counts
28 (58.33%) (29.17%) (15.14%) 24.91
20 (41.67%) (22.47%) (10.81%) 23.09
No
% within Cancer
% within Aspirin Taker
% of Total
Expected Counts
68 (49.64%) (70.83%) (36.76%) 71.09
69 (50.36%) (77.53%) (37.3%) 65.91
b.
Room Type
Infection
Concrete
Linoleum
Yes
% within Infection
% within Room Type
% of Total
Expected Counts
2 (9.091%) (5.882%) (1.626%) 6.08
20 (90.91%) (22.47%) (16.26%)
15.9
No
% within Infection
% within Room Type
% of Total
Expected Counts
32 (31.68%) (94.12%) (26.02%) 27.9
69 (68.32%) (77.53%) (56.1%) 73.1
c.
Smoker
Diabetes
No
Yes
Yes
% within Diabetes
% within Smoker
% of Total
Expected Counts
2 (25%) (4.878%) (2.439%) 4
6 (75%) (14.63%) (7.317%) 4
No
% within Diabetes
% within Smoker
% of Total
Expected Counts
39 (52.7%) (95.12