RMB (2)

Qualitative Surveys and Thematic Analysis

• Participants in qualitative surveys have increased control over their responses, allowing for richer data collection.
• Thematic analysis is a qualitative research method used to identify, analyze, and report patterns (themes) within data.

Epistemology Categories

• Three categories of epistemology:
  • Positivism: Emphasis on observable, objective facts.
  • Interpretivism: Focus on understanding the subjective meaning of social phenomena.
  • Critical theory: Examines social structures and challenges power dynamics.

Interpretative Phenomenological Analysis (IPA)

• IPA acknowledges the researcher's subjectivity by recognizing their role in interpreting participants’ experiences, emphasizing a co-construction of meaning.

Asynchronous Online Groups

• Asynchronous online groups involve participants engaging at different times, facilitating flexibility in discussion and allowing for thoughtful responses.

Media Data Utilization

• Media data is valuable as it provides rich, multifaceted information, revealing insights into public sentiments, behaviors, and trends.

Reporting Mann-Whitney Results

• In APA format, report the U statistic, p-value, and sample sizes for each group being compared.

Understanding N in Research

• N represents the sample size, indicating the number of observations or participants in the study.

Wilcoxon Signed Rank Test Reporting

• Report the W statistic, p-value, and the number of pairs in the Wilcoxon signed rank test results.

Experimental Designs in Dependent T-Tests

• Within-subjects designs (where the same participants are tested under different conditions) can be used in dependent t-tests.

Reporting Values in T-Tests

• In all t-tests, report the t statistic, degrees of freedom, and p-value.

High Correlation in Dependent Tests

• A high correlation in dependent t-tests indicates a strong relationship between the paired observations, suggesting that changes in one variable relate to changes in another.

Defining Effect Size

• Effect size quantifies the size of the difference between groups, providing context to the significance of results beyond p-values.

Preference for Effect Size

• Effect size is preferred over statistical significance, as it conveys practical implications of research findings.

Pearson's r Correlation Effect Sizes

• Small: 0.10
• Medium: 0.30
• Large: 0.50

Cohen's d Effect Sizes

• Small: 0.2
• Medium: 0.5
• Large: 0.8

Use of Exact and Asymptotic Significance

• Exact significance is preferred for small sample sizes due to its accuracy, while asymptotic significance is used for larger sample sizes where approximations are sufficient.

Test your knowledge on effect sizes and correlations with this quiz. Explore the reporting values for T tests, the meaning of high correlation in a dependent test, and the significance of effect size over statistical significance. Assess your understanding of small, medium, and large effect sizes for Pearson's r and Cohen's d.