Difference Inferential Statistics
Title: Significant Difference Inferential Statistics
Case Assignment
Based on your proposed DSP topic and construct(s)/variable(s) of interest, write a Research Question and Hypotheses (null and alternate) that reflect the need to conduct a t-test OR ANOVA OR other related “comparative difference” statistic in order to test the hypotheses. Include detailed information regarding t-test OR ANOVA OR other specified “comparative difference” application and data results.
Required Reading
Brown, J. (2022). Analyzing quantitative data. Mixed methods research for TESOL (pp. 63-90). Edinburgh University Press. Available in the Trident Online Library.
Huberty, C. J., & Morris, J. D. (1992). Multivariate analysis versus multiple univariate analyses. In A. E. Kazdin (Ed.), Methodological issues & strategies in clinical research (pp. 351-365). American Psychological Association. Available in the Trident Online Library.
Mackridge, A., & Rowe, P. (2018). One?Way analysis of Variance (ANOVA) – Including Dunnett’s and Tukey’s follow-up tests. In A. Mackridge, & P. Rowe (Eds.), A practical approach to using statistics in health research (pp. 93-103). John Wiley & Sons. Available in the Trident Online Library.
Scott, I., & Mazhindu, D. (2005). Non-parametric tests. Statistics for health care professionals SAGE Publications, Ltd. pp.148-164 Available in the Trident Online Library.
Case 2 Feedback:
Overall Feedback
Your paper is thorough, well-structured, and clearly connects Pearson correlation to your DSP goals. You do an excellent job explaining the rationale, hypotheses, and interpretation of r values in both statistical and operational terms. To further strengthen your work: (1) Streamline repetitive definitions of r to keep focus on your specific context. (2) When discussing assumptions, briefly note how you will test them (e.g., histograms, Shapiro–Wilk). (3) In your examples, add effect size interpretation and possibly confidence intervals for completeness. (4) In your DSP implications, highlight why readiness compliance is critical to operational readiness to reinforce significance. (5) Review formatting for consistency in H?/H? notation. Overall, this is a strong, relevant, and clearly articulated analysis plan.
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