One of the more challenging aspects of data analysis is determining which statistical tests to run (given the circumstances) and how to perform the SPSS steps correctly. There are several type of decision trees you can use to select a statistical test, but we will look at just one type in this assignment.
At the most fundamental level, statistical tests are usually chosen according to:
- The nature of the data you have collected to answer the research question in your study (nominal, ordinal, or interval/ratio).
- The number of samples being analyzed for a given variable (often described by groupings).
- What you wish the test to do (find differences between samples/groups, explore relationships between variables, make predictions using different variables).
Before choosing a test for interval/ratio data, there is one final characteristic of the data that must be determined, which is whether the data is "normally" distributed. If the data distribution violates the assumption of normality, a nonparametric equivalent test must be selected for the analysis.
There are many other issues that can influence the analytical technique (sample size, variability of the data, inter-relatedness of the variables, et cetera), but these challenges are for another time, another course.
You are encouraged to review the t-test and ANOVA materials from previous units. Then, examine How to Choose a Statistical Test and the test-selection tutorials linked in the Resources to determine which statistical test is most likely to be appropriate for your data type.
Use SPSS and the Framingham study data set to perform and interpret statistical tests that answer the following research questions. Then, provide a written analysis of your results.
First, test the normal distribution assumption and select the appropriate statistical analysis path. Next, compare men and women in the Framingham study to determine whether there was a significant difference in baseline cholesterol levels (variable: totchol1).
Create four BMI categories:
- Underweight: < 18.5.
- Normal: 18.5–25.
- Overweight: 25–30.
- Obese: > 30.
Without testing for the assumption of normal distribution of data, use the four BMI categories you created and compare baseline glucose levels (variable: glucose1) to determine if there is a significant difference across these four categories.
- First, test the normal distribution assumption and select the appropriate statistical analysis path.
- Next, determine whether there a significant difference in baseline heart rate (variable: heartrte1) between smokers and nonsmokers.
Written Analysis Format and Length
Format your analysis using APA style.
- Use the APA Style Paper Template, linked in the Resources. An APA Style Paper Tutorial is also provided to help you in writing and formatting your analysis.
- Your analysis should be 2–3 pages in length, not including the title page and references page.
Note: The requirements outlined below correspond to the grading criteria in the scoring guide. Be sure that your statistical analysis addresses each point, at a minimum. You may also want to read the Testing to Find Differences Between Groups Scoring Guide to better understand how each criterion will be assessed.
Perform the appropriate statistical tests (based on the assumption test).
- Provide your rationale for test selection.
Interpret the results of your statistical tests (t tests, ANOVA) for each research question.
- Consider associated caveats and limitations.
Determine the practical, public health-related implications of your statistical tests (t tests, ANOVA).
- What evidence do you have that validates your conclusions?
Write clearly and concisely, using correct grammar, mechanics, and APA formatting.
- Write for an academic audience, using appropriate statistical terminology, style, and form.
- Express your main points and conclusions coherently.
- Proofread your writing to minimize errors that could distract readers and make it more difficult for them to focus on the substance of your statistical analysis.
Submit appropriately labeled SPSS results output files (.spv), along with your written analysis.
Include the test results and associated graphic in your written analysis (copied from the output file and pasted into a Word document). Refer to How to Copy SPSS Output and Paste It Into a Word Document, linked in the Resources.