scientist

Hypothesis testing evaluates whether observed patterns in your data are statistically significant or due to chance. This Skill applies scipy and scikit-learn to compute p-values, confidence intervals, and effect sizes across your structured data, producing rigorous conclusions for business and research datasets.

Yes. This Skill fits regression models using SciPy and scikit-learn, computing confidence intervals and effect sizes to quantify relationships between variables. You provide a CSV or structured dataset and receive fitted models with statistical validation metrics.

Correlation analysis identifies relationships between variables in your dataset. This Skill computes correlations, fits regression models, and generates advanced visualizations with confidence intervals and p-values to surface trends and key drivers in sales or business data.

Quality gates enforcement validates that your analysis satisfies requirements for sample size, confidence intervals, and statistical significance. This Skill applies these checks automatically, ensuring your conclusions rest on rigorous statistical foundations.

This Skill applies standardized statistical methods across datasets of varying scale. It computes sample sizes, confidence intervals, and p-values to ensure conclusions remain valid regardless of dataset size, supporting both research and business analysis contexts.