Regression Forecasting Assistant

Pro v1.0.0 1 view

Build validated regression models for business forecasting with automatic assumption checking, diagnostic plots, confidence intervals, and extrapolation warnings.

What You Get

Get production-ready regression models with validated assumptions, diagnostic visualizations, and properly quantified uncertainty for business decision-making.

The Problem

Building reliable regression models for business forecasting requires checking statistical assumptions, generating diagnostic plots, and properly quantifying uncertainty. Without proper validation, forecasts can be misleading and lead to poor business decisions. Most analysts skip assumption checks or don't know how to interpret violations.

The Solution

This skill guides you through a complete regression modeling workflow: fit linear or polynomial models using statsmodels OLS, validate all critical assumptions (linearity, homoscedasticity, normality, independence), generate diagnostic plots, produce forecasts with confidence and prediction intervals, and deliver business-focused insights. It emphasizes the critical distinction between correlation and causation, warns about extrapolation risks, and provides actionable recommendations.

How It Works

  1. 1 Load data and perform exploratory analysis with statistics and scatter plots
  2. 2 Validate data quality: sample size, missing values, outliers, variance checks
  3. 3 Fit regression model (linear or polynomial) and display coefficients with significance tests
  4. 4 Check model assumptions: linearity, homoscedasticity, normality, independence
  5. 5 Generate 4-panel diagnostic plots: residuals vs fitted, Q-Q, scale-location, actual vs predicted
  6. 6 Produce forecasts with 95% confidence and prediction intervals, flagging extrapolation
  7. 7 Deliver business insights with model quality assessment, limitations, and recommendations

What You'll Need

  • Python with statsmodels, scipy, matplotlib, pandas, and numpy
  • Tabular data with at least 10-12 observations for simple regression
  • Clear dependent and independent variables with sufficient variance
  • Business context for interpreting results

Get This Skill

Requires Pro subscription ($9/month)

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