State a clear hypothesis and give a plausible rationale for it.

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This data can be found on SPSS
Assignment #4: Data analysis . In your toolkits, students are supplied with two data sets: SMI data is cross sectional and allows for some bivariate statistical tests; OPS data also allows for the paired t-test since it is longitudinal and allows for pre-post testing.
There are two parts to this assignment:
PART I: Using the SMI data set, students will test two different hypotheses using either a correlation, chi square, or independent t-test. Students should use a different test each hypothesis (for example, a Pearson correlation and a t-test.
PART II: students will test two hypotheses both of which will be tested with a paired t-test using the OPS data set.
PART I: Using the “SMI” data set , conduct two separate analyses for two different hypotheses. The tests may include a correlation, t-test, or chi square, but you must use two different statistical tests (e.g., a Pearson correlation and a t-test).
For each test, explain what you did for each of the following steps and show relevant output:
1. State a clear hypothesis and give a plausible rationale for it.
2. Run frequencies on the relevant variables and report the measures of central tendency (only for continuous variables); describe the distributional characteristics (show output).
3. State the test you are going to perform (i.e., Pearson’s r or Spearman’s rho, t-test, chi square) and why you selected that test (i.e., how data meets assumptions of the test)
4. Describe any transformations of variables (i.e., computes or recodes).
5. Run the test (show syntax and output).
6. Interpret the results in reference to your hypothesis.
PART II: Using the “OPS” data set , use paired t-tests to test two separate hypotheses about the relationship between baseline and outcome measures (pre-post). Follow the same steps as you did in PART I as follows and show all relevant output.

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