DSRT 734: Testing Gender and COVID Diagnosis in JASP

DSRT 734 Question

A researcher wanted to test if gender had an significant impact on a
Covid diagnosis. Download the attached dataset and open it in JASP.
Run the correct test, copy your output into the answer blank, and write
your conclusion in APA format.

What this question assesses

This assignment assesses translation of two categorical variables into a contingency analysis, selection based on table conditions, and interpretation that distinguishes association from a causal “impact” claim.

How to approach this type of question

The attachment is required to know categories, counts, missingness, and expected frequencies. With the file, verify the coding of gender and COVID diagnosis, document any unknown or missing categories, and ensure one row represents one independent person. Produce a contingency table with observed counts and, where supported, expected counts and row or column percentages. In JASP, choose a categorical association analysis and inspect expected-cell diagnostics before deciding whether the ordinary chi-square approximation or an exact alternative is appropriate. Request a suitable effect-size measure if the course workflow includes it. Record the statistic, degrees of freedom when applicable, p-value, sample size, and table percentages. In the final interpretation, use association language unless the design supports causal inference; the word “impact” in the prompt is not itself evidence of causation. Without the dataset, no output or APA conclusion can be reproduced.

A reproducible analysis note should record category coding, contingency-table orientation, analyzed N, expected-count diagnostics, selected test, and the reported association measure. Verify that “Covid diagnosis” is not miscoded as a numeric continuous outcome merely because software represents categories with numbers. If more than two gender or diagnosis categories appear, reassess the table and method rather than silently dropping records. The final APA wording must be generated from the real output and preserve uncertainty. Report which percentages are row-based or column-based so readers can audit the prevalence comparison.

Related DSRT 734 questions

• DSRT 734: Choosing a Test for Disease Prevalence by Gender
• DSRT 734: Choosing a Test for Gender and Disease
• DSRT 734: Testing Chronic Disease Prevalence by Gender in JASP

Related DSRT 734 resources

• University of the Cumberlands course resources
• DSRT 734 Inferential Statistics in Decision-Making
• DSRT 734 Questions: Inferential Statistics in Decision-Making
• How to Choose an Inferential Statistical Test