Student must have a basic understanding of statistical measurements and how they apply within the parameters of data management and analytics.
Use of APA-7 style is required
This assignment uses a rubric. Review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion.
Required to submit to Turnitin
Use of minimum of 4 scholarly peer-reviewed resources published within past 3 years is required.
1. Write a data analysis paper outlining the procedures used to analyze the parametric and non-parametric variables in the mock data, the statistics reported, and a conclusion of the results.
Provide a conclusive result of the data analyses based on the guidelines below for statistical significance.
1. PAIRED SAMPLE T-TEST: (variables BaselineWeight and InterventionWeight). Report the mean weights, standard deviations, t-statistic, degrees of freedom, and p level. Report as t(df)=value, p = value. Report the p level out three digits.
2. INDEPENDENT SAMPLE T-TEST: (variables InterventionGroups and PatientWeight). Report the mean weights, standard deviations, t-statistic, degrees of freedom, and p level. Report t(df)=value, p = value. Report the p level out three digits
3. CHI-SQUARE (Independent): (variables BaselineReadmission and InterventionReadmission). Report the frequencies of the total events, the chi-square statistic, degrees of freedom, and p level. Report 2 (df) =value, p =value. Report the p level out three digits.
4. MCNEMAR (Paired): (variables BaselineCompliance and InterventionCompliance). Report the frequencies of the events, the Chi-square, and the McNemars p level. Report (p =value). Report the p level out three digits.
5. MANN WHITNEY U: (variables InterventionGroups and PatientSatisfaction). Report the Medians or Means, the Mann Whitney U statistic, and the p level. Report (U =value, p =value). Report the p level out three digits.
6. WILCOXON Z: (variables BaselineWeight and InterventionWeight). Report the Mean or Median weights, standard deviations, Z-statistic, and p level. Report as (Z =value, p =value). Report the p level out three digits.
Include the following in your paper:
1. Discussion of the types of statistical tests used and why they have been chosen.
2. Discussion of the differences between parametric and non-parametric tests.
3. Summary of the conclusive result of the data analyses.
Use the following guidelines to report the test results:
Statistically Significant Difference: When reporting exact p values, state early in the data analysis and results section, the alpha level used for the significance criterion for all tests in the project. Example: An alpha or significance level of < .05 was used for all statistical tests in the project. Then if the p-level is less than this value identified, the result is considered statistically significant. A statistically significant difference was noted between the scores before compared to after the intervention t(24) = 2.37, p = .007.
Marginally Significant Difference: If the results are found in the predicted direction but are not statistically significant, indicate that results were marginally significant. Example: Scores indicated a marginally significant preference for the intervention group (M = 3.54, SD = 1.20) compared to the baseline (M = 3.10, SD = .90), t(24) = 1.37, p = .07. Or there was a marginal difference in readmissions before (15) compared to after (10) the intervention 2(1) = 4.75, p = .06.
Non-Significant Trend: If the p-value is over .10, report results revealed a non-significant trend in the predicted direction. Example: Results indicated a non-significant trend for the intervention group (14) over the baseline (12), 2(1) = 1.75, p = .26.