This is the abstract for the Corwin article in which the RENAL.sav file was collected and analyzed. The citation is in the back of the Norusis text. The RENAL.sav file will be used for both the mid-term AND final projects.

We performed a case-control study to identify risk factors for the development of acute renal failure after cardiac operations. Forty-two cases of acute renal failure were identified in a total of 572 patients who underwent cardiac operations. They were matched with a control population of patients having cardiac operations without acute renal failure. Discriminant analysis performed with preoperative variables revealed preoperative serum creatinine values, concurrent valve and bypass surgery, and age to be significant variables for identifying patients at risk for acute renal failure. The use of these three variables in a discriminant model correctly classified 77% of patients. The addition of intraoperative variables did not significantly improve the ability of the model to correctly classify patients. Acute renal failure was associated with a significant increase in the number of postoperative complications, mortality, and length of hospitalization and intensive care unit stay.

OM7080 FINAL COURSE PROJECT – Hypothesis Testing

For the FINAL PROJECT, you must do the following:

1) Independent Samples t-test

�� Choose any scale variable and any nominal variable with two levels from the RENAL.sav file (e.g., GENDER, DIABETES, ALIVE, BYPASS, etc.).

�� Write out the assumptions for the Independent Samples t-testand evaluate that the variables are appropriate for the test (if not, you must select another set of variables).

�� State the hypothesis to be tested.

�� Test for the equality of variances before proceeding.

�� Conduct an Independent Samples t-test on the scale variable with the nominal variable as a grouping variable.

�� State the reject / not reject decision and conclusion.

�� State any insights (in English) you can draw from the results; if you reject the null, your insights should follow from the conclusion, and if you fail to reject the null, then your insight should be non-conclusive but possibly offering thoughts about why the results were as they were and whether it makes intuitive sense.

2) One-Way ANOVA

�� Create a new variable AGE3 in which ages from 0-59 are recoded as a 1, ages 60-69 are recoded as a 2, and ages 70 and older are recoded as a 3.

�� Choose any scale variable from the RENAL.sav file.

�� Write out the assumptions for the ANOVA and evaluate that the variables are appropriate for the test (if not, you must select another set of variables).

�� State the hypothesis to be tested.

�� Conduct a One-Way ANOVA on the scale variable with AGE3 as a factor. Use the Bonferroni Post Hoc test as appropriate.

�� State the reject / not reject decision and conclusion.

�� State any insights (in English) you can draw from the results; if you reject the null, your insights should follow from the conclusion, and if you fail to reject the null, then your insight should be non-conclusive but possibly offering thoughts about why the results were as they were and whether it makes intuitive sense.

3) Mann-WhitneyU test

�� Choose any scale variable and any nominal variable with two levels from the RENAL.sav file (e.g., GENDER, DIABETES, ALIVE, BYPASS, etc.).

�� Write out the assumptions for the Mann-Whitney Utest.

�� State the hypothesis to be tested.

�� Conduct a Mann WhitneyU test on the scale variable with the nominal variable as a grouping variable.

�� State the reject / not reject decision and conclusion.

�� State any insights (in English) you can draw from the results; if you reject the null, your insights should follow from the conclusion, and if you fail to reject the null, then your insight should be non-conclusive but possibly offering thoughts about why the results were as they were and whether it makes intuitive sense.

4) Kruskal-Wallis H test

�� Use the AGE3 variable from the ANOVA you performed.

�� Choose any scale variable from the RENAL.sav file.

�� Write out the assumptions for the Kruskal-Wallis test.

�� State the hypothesis to be tested.

�� Conduct a Kruskal-Wallis H test on the scale variable with AGE3 as a factor.

�� State the reject / not reject decision and conclusion.

�� State any insights (in English) you can draw from the results; if you reject the null, your insights should follow from the conclusion, and if you fail to reject the null, then your insight should be non-conclusive but possibly offering thoughts about why the results were as they were and whether it makes intuitive sense.

5) Chi Square test

�� Choose any two nominal variables from the RENAL.sav file.

�� Write out the assumptions for the Chi Square test.

�� State the hypothesis to be tested.

�� Create a Cross-tabulation of the two nominal variables.

�� Compute the Chi-Square, Lambda and Gamma.

�� Discuss the computed values of Lambda and Gamma.

�� State the reject / not reject decision and conclusion.

�� State any insights (in English) you can draw from the results; if you reject the null, your insights should follow from the conclusion, and if you fail to reject the null, then your insight should be non-conclusive but possibly offering thoughts about why the results were as they were and whether it makes intuitive sense.

6) Regression analysis.

�� Choose any two scale variables from the RENAL.sav file.

�� Write out the assumptions for the Regression Analysis.

�� Conduct tests for the assumptions; evaluate the assumptions by analyzing the residuals.

�� Create a scatterplot with regression line.

�� State the hypothesis to be tested.

�� Conduct a linear regressionanalysis and test for correlation.

�� Discuss the computed R, R-squared and the regression model.

�� State the reject / not reject decision and conclusion.

�� State any insights (in English) you can draw from the results; if you reject the null, your insights should follow from the conclusion, and if you fail to reject the null, then your insight should be non-conclusive but possibly offering thoughts about why the results were as they were and whether it makes intuitive sense.

Note: Please choose variables that you actually understand

In the MS Word document, you should do the following:

? Number each section as shown above

? State the variables you are analyzing before each section.

? Paste the SPSS output into each section.

? Add a brief analysis of the output. This should be a brief write-up (probably about one or two pages) of what you can conclude from the output and any insights you might have in general, given all of the tests you conducted on variables you selected. Basically, tie everything together, as you would in a dissertation. Try to relate the results to what limited knowledge you may have of heart failure and other health problems.

? Disregard APA rules for this paper, but adhere to the rules of grammar / spelling / punctuation.

The solution provides step by step method for the regression analysis and hypothesis testing in SPSS . Formula for the calculation and Interpretations of the results are also included.