What problem does it solve?
Provides practical, business-focused statistical guidance to summarize metrics, detect anomalies, evaluate trends, and avoid common misinterpretations so stakeholders can make informed decisions without overclaiming certainty.
Core Features & Use Cases
- Descriptive summaries: Recommend mean, median, IQR, standard deviation, coefficient of variation, and key percentiles to characterize distributions.
- Trend analysis & forecasting: Explain moving averages, period-over-period comparisons, simple naive and seasonal forecasts, and when to escalate to advanced modeling.
- Outlier and anomaly detection: Present z-score, IQR, and percentile methods for point anomalies and residual-based approaches for time series anomalies.
- Hypothesis testing guidance: Advise on test selection (t-test, proportions, ANOVA, nonparametric), significance versus practical importance, confidence intervals, and sample size considerations.
- Use case: Rapidly assess whether a change in conversion rate or session duration is meaningful, identify extreme users, and produce actionable summaries for product or marketing teams.
Quick Start
Analyze the attached dataset and report mean, median, IQR, p50/p75/p90/p95, flag outliers, show a 7-day moving average for trends, and state whether results warrant escalation to a data scientist.
