statistical▌

Statistical methods for descriptive analysis, trend detection, outlier identification, and hypothesis testing with practical business interpretation. \n \n Covers descriptive statistics (mean, median, percentiles, spread measures), trend analysis with moving averages and period-over-period comparisons, and simple forecasting methods for business analysts \n Includes three outlier detection approaches (z-score, IQR, percentile methods) with guidance on investigating and handling anomalies rather

Comprehensive statistical modeling skill for fitting regression models, survival models, and mixed-effects models to biomedical data. Produces publication-quality statistical summaries with odds ratios, hazard ratios, confidence intervals, and p-values.

Statistical analysis is a systematic process for testing hypotheses and quantifying relationships. Conduct hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, and Bayesian analyses with assumption checks and APA reporting. Apply this skill for academic research.

Hypothesis testing provides a framework for making data-driven decisions by testing whether observed differences are statistically significant or due to chance.