statistical-analysis

To generate APA-formatted reports for hypothesis testing, this Skill automates the execution of statistical tests andoutputs publication-ready results. It calculates effect sizes and produces professional reports directly from your observational or experimental data.

To check statistical assumptions like normality before running a t-test, this Skill automates the verification process with built-in visualizations. It evaluates data distribution and variance requirements to recommend the appropriate statistical tests.

Yes, you can use Python for guided Bayesian analysis and regression on survey data. This Skill utilizes libraries like PyMC and statsmodels to execute Bayesian inference, correlation, and regression analyses while providing automated guidance.

The best way to select the right statistical test for your research data is through guided test selection. This Skill evaluates your research questions and data structure to recommend appropriate statistical hypothesis tests for academic research.

You need pandas and scipy to perform statistical hypothesis testing because this Skill depends on them for data manipulation and scientific computing. These libraries provide the foundational environment for executing the automated assumption checks and statistical analyses.