Using the provided dataset from SLP 1, calculate the appropriate descriptive statistics for the following variables, comparing diabetes with no diabetes status: gender, race, salary, education, height, weight, BMI, allergies, family history diabetes, family history allergies. For chi-square tests, report the chi-square value and the p-value (if p-value < 0.05, then the test is significant). For t-tests, report the t-test value and the p-value. Include a 2- to 3-page description of the descriptive statistics, including tables of the summarized data. This is similar to a “Results” section in a published manuscript or journal article. Use the following online calculators to obtain the results for this analysis. Chi-Square for Categorical Data: http://www.vassarstats.net/ Choose “Frequency Data” from the far left, then “Chi-Square, Cramer’s V, and Lambda” from the middle of the page. Enter in the number of people in each category (e.g., number of women who have diabetes, number of men with diabetes, etc.). Example of a table below: Diabetes No Diabetes Female 86 214 Male 36 264 Choose a 2 x 2 table and where A1 = 86, A2 = 36; B1 = 214; B2 = 264. Report the percent of people in each category and the chi-square and p-value. A possible sentence to interpret the results could be: There are significantly more women (64%) who have diabetes than men (36%). T-Tests for Continuous Data: http://www.vassarstats.net/ Choose “T-Tests & Procedure” from the far left, then “Two-Sample t-Test”, then click “Independent Samples” under Setup. Copy and Paste the values for those with diabetes into Sample A and those without diabetes into Sample B, then click Calculate. For instance, copy and paste all of the ages of those with diabetes into Sample A and all of the ages of those without diabetes into Sample B. From the Data Summary window, report the Mean of those with Diabetes (Sample A) and those without Diabetes (Sample B); also report the “t” from the Results box, as well as the two-tailed p-value. A “p” that is <0.05 suggests that the result is statistically significant. One way to report such a finding would be to use the following language: The average age of those with diabetes is __ years and for those without diabetes, the average is __ years. Those with diabetes were significantly older/younger (p<0.05).
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