Testing Hypotheses Of Perceived CAP Learning Rovai 2009 Data


Research has shown that males and females differ in their community connectedness, learning community, and perceived learning (Rovai & Baker, 2005). Females feel more connected to other students in their courses, and their online learning experiences are more aligned to their educational values and goals when compared to their male peers. So, the researcher wants to know if the sample he is examining is similar to other research samples, so he questions if males and females in this data set differ across the measures of effectiveness gathered. Understanding this could inform further analyses. Thus, the first analysis that the researcher desires for you to run is aimed at answering the following question: What is the difference in students' perceived learning score as measured by the Perceived CAP Learning Scale (Rovai et al., 2009) based on their gender? What analysis needs to be run to answer this question and what are the results? 

Include the following elements in the results section:

  1. The assumption tests and their results, including a conclusion about the tenability of the assumption and how it may influence the results (include graphs if you used them);
  2. Adequate descriptive statistics (e.g. M, SD, n, N);
  3. The null hypothesis;
  4. Identification of the appropriate t test and a justification for its use using analysis resources;
  5. The results of the t test, in statistical and narrative form;
  6. The decision regarding the null hypothesis; and
  7. The effect size, including an interpretation (be sure to cite the convention used), and confidence interval.



The question belongs to Statistics and it discusses about performing hypotheses testing with data from Perceived CAP Learning Scale (Rovai et al, 2009).

Total Word Count 230


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