Chi-squared test

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Chi-squared test

Study interpretation and drawing conclusions from data

Bias, confounding, and threats to validity

Bias in interpreting results of clinical studies
Bias in performing clinical studies
Confounding
Information bias
Interaction
Selection bias

Causation

Disease causality

Chance

Hypothesis testing: One-tailed and two-tailed tests
Chi-squared test
Fisher's exact test
Kappa coefficient
Mann-Whitney U test
Spearman's rank correlation coefficient
One-way ANOVA
Paired t-test
Repeated measures ANOVA
Two-sample t-test
Two-way ANOVA
Type I and type II errors

Key Takeaways

The chi-squared test is a statistical method used to test the independence of two categorical variables. The chi-squared statistic is calculated as the sum of the squared differences between the observed and expected frequencies for each category, divided by the number of degrees of freedom.