Solved by verified expert:331 EXERCISE 29 Questions to Be Graded Name: _______________________________________________________ Class: ________________________________________________________________________________________________________ Follow your instructor’s directions to submit your answers to the following questions for grading. Your instructor may ask you to write your answers below and submit them as a hard copy for grading. Alternatively, your instructor may ask you to use the space below for notes and submit your answers online at http://evolve.elsevier.com/Grove/Statistics/ under “Questions to Be Graded.” 1. If you have access to SPSS, compute the Shapiro-Wilk test of normality for the variable age (as demonstrated in Exercise 26). If you do not have access to SPSS, plot the frequency distributions by hand. What do the results indicate? 2. State the null hypothesis where age at enrollment is used to predict the time for completion of an RN to BSN program. 3. What is b as computed by hand (or using SPSS)? 4. What is a as computed by hand (or using SPSS)? 332 5. Write the new regression equation. 6. How would you characterize the magnitude of the obtained R2 value? Provide a rationale for your answer. 7. How much variance in months to RN to BSN program completion is explained by knowing the student’s enrollment age? 8. What was the correlation between the actual y values and the predicted y values using the new regression equation in the example? 9. Write your interpretation of the results as you would in an APA-formatted journal. 10. Given the results of your analyses, would you use the calculated regression equation to predict future students’ program completion time by using enrollment age as x? Provide a rationale for your answer. (Grove 330-332) Grove, Susan K., Daisha Cipher. Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition. Saunders, 022016. VitalBook file. The citation provided is a guideline. Please check each citation for accuracy before use. Totals 15 82 97 419 EXERCISE 35 Questions to Be Graded Name: _______________________________________________________ Class: _____________________ Date: ___________________________________________________________________________________ Follow your instructor’s directions to submit your answers to the following questions for grading. Your instructor may ask you to write your answers below and submit them as a hard copy for grading. Alternatively, your instructor may ask you to use the space below for notes and submit your answers online at http://evolve.elsevier.com/Grove/statistics/ under “Questions to Be Graded.” 1. Do the example data in Table 35-2 meet the assumptions for the Pearson χ2 test? Provide a rationale for your answer. 2. Compute the χ2 test. What is the χ2 value? 3. Is the χ2 significant at α = 0.05? Specify how you arrived at your answer. 4. If using SPSS, what is the exact likelihood of obtaining the χ2 value at least as extreme as or as close to the one that was actually observed, assuming that the null hypothesis is true? 420 5. Using the numbers in the contingency table, calculate the percentage of antibiotic users who tested positive for candiduria. 6. Using the numbers in the contingency table, calculate the percentage of non-antibiotic users who tested positive for candiduria. 7. Using the numbers in the contingency table, calculate the percentage of veterans with candiduria who had a history of antibiotic use. 8. Using the numbers in the contingency table, calculate the percentage of veterans with candiduria who had no history of antibiotic use. 9. Write your interpretation of the results as you would in an APA-formatted journal. 10. Was the sample size adequate to detect differences between the two groups in this example? Provide a rationale for your answer. (Grove 418-420) Grove, Susan K., Daisha Cipher. Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition. Saunders, 022016. VitalBook file. The citation provided is a guideline. Please check each citation for accuracy before use.
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