Linear Regression for Analysts

Summary

Extending Phase 4's regression basics into an actual predictive tool — fitting a line (or hyperplane) to predict a continuous outcome from one or more input variables.

How to Learn This

1Fit a simple linear regression in Python (or Excel) predicting one variable from another.
2Learn to sanity-check a regression's coefficients against real-world intuition.
3Understand the core assumptions (linearity, independence) well enough to know when they're violated.

Intro to Predictive Analytics

Logistic Regression Basics

More topics in Advanced Analytics & Predictive Basics

Intro to Predictive Analytics Logistic Regression Basics Time Series Analysis Basics Clustering Basics (K-Means Overview)Intro to Machine Learning for Analysts When to Escalate to a Data Scientist Forecasting Fundamentals

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