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statistical-analysis

Analyze datasets with descriptive statistics, trend analysis, anomaly detection, and hypothesis testing.

Updated Jan 11, 2026
Search Tags:#data-analysis#anomaly-detection#hypothesis-testing#statistical-analysis#trend-analysis#descriptive-statistics#business-intelligence
One-click install
npx skills add https://github.com/chelleboyer/reachy_mini_retail_assistant --skill statistical-analysis-chelleboyer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: statistical-analysis
Source: https://github.com/chelleboyer/reachy_mini_retail_assistant/tree/main/skills/data/skills/statistical-analysis
Command: npx skills add https://github.com/chelleboyer/reachy_mini_retail_assistant --skill statistical-analysis-chelleboyer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps teams make sense of data by applying descriptive statistics, trend analyses, outlier detection, and hypothesis testing to interpret distributions, detect anomalies, and draw evidence-based conclusions.

Core Features & Use Cases

  • Descriptive statistics to summarize central tendency and variability.
  • Trend analysis and forecasting basics to identify patterns and project trajectory.
  • Outlier detection and anomaly reporting to flag unusual observations.
  • Hypothesis testing guidance with practical cautions to assess significance.
  • Narratives and dashboards support to communicate results with business impact.

Quick Start

Ask the skill to analyze your latest dataset to produce a concise statistical summary and actionable insights.

Frequently Asked Questions about statistical-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I calculate descriptive statistics and central tendency for my dataset?▼

Descriptive statistics summarize your dataset's central tendency and variability to identify distribution patterns. This skill computes these measures to provide a concise statistical summary of your business metrics.

What is the best way to detect anomalies and outliers in operational dashboards?▼

Anomaly detection flags unusual observations in operational dashboards by identifying statistical outliers. This skill analyzes your data distributions to report anomalies and highlight data points deviating from expected trends.

How do I run hypothesis testing to assess the significance of my business metrics?▼

Hypothesis testing assesses the statistical significance of business metrics by evaluating distributions and relationships. This skill guides you through testing while providing practical cautions and caveats regarding the results.

Can I use trend analysis to identify patterns and forecast trajectories in research datasets?▼

Trend analysis identifies patterns within research datasets to project future trajectories. This skill applies trend analysis and forecasting basics to your data, helping interpret historical patterns and communicate actionable insights.

Does this statistical analysis approach support business intelligence reporting without external dependencies?▼

Statistical analysis for business intelligence reporting is supported without external dependencies. This skill operates independently to derive evidence-based conclusions, enabling dashboards and narratives with practical business impact.

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