Statistical Analysis

Apply stats methods: descriptive stats, trend analysis, outlier detection, hypothesis testing.

statistics hypothesis-testing regression analysis

When to use

Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results. Covers descriptive stats, trend analysis, outlier detection, and hypothesis testing with plain-English interpretation.

Examples

A/B test significance

Determine if an experiment result is statistically significant

Is this A/B test result significant? Control: 4.2% CVR, 5,200 visitors. Variant: 4.9% CVR, 5,100 visitors.

Outlier detection

Find anomalous data points in a dataset

Detect outliers in our transaction data. We suspect some values are data entry errors vs. genuine high-value orders.

Trend analysis

Analyze a metric's trend over time

Analyze the trend in our monthly churn rate over the past 18 months. Is the recent increase statistically meaningful?