statistical-analysis

To choose the right statistical test, you must evaluate your data characteristics and research question. This skill guides researchers through selecting appropriate frequentist or Bayesian tests, such as t-tests, ANOVA, or regression, based on specific data inputs.

Checking statistical assumptions requires verifying conditions like normality and homogeneity before running tests like ANOVA. This skill provides guided workflows to help researchers check these assumptions, ensuring the rigor of scientific studies and reducing analytical errors.

To report statistical results in APA style, you need accurate formatting and effect size interpretation. This skill assists researchers in calculating effect sizes and generating APA style reports for frequentist and Bayesian methods.

You can use Bayesian hypothesis testing as an alternative to frequentist methods. This skill supports both approaches, guiding you through test selection, assumption checking, and result interpretation for common statistical tests including t-tests and ANOVA.

Prior statistical knowledge is required because this skill demands an understanding of statistical principles and data characteristics. It uses this foundation to guide the correct application of tests, verify assumptions, and interpret effect sizes accurately.