Regression Analysis for Business in Excel
From scatter plot to multiple regression: least squares by hand, R² and standard error, t-tests and p-values, prediction intervals, LINEST with several drivers, dummy variables, residual analysis and log models, in 8 hands-on labs on one retailer's data.
The first lesson is free — no account needed.
About this course
A regression analysis course in Excel that goes from a scatter plot to multiple regression on one retailer's store data, for analysts, students and anyone who has to defend a forecast. You measure correlation by hand and with CORREL, fit a simple regression line from sums of squares and check it against Excel's built-in functions, test whether a slope is real with its t statistic, p-value and 95% confidence interval, put a prediction interval around the forecast for a new store, fit three drivers at once with LINEST and read each coefficient with INDEX, turn regions and seasons into dummy variables, check residuals and standardised residuals for outliers and fit a log-log demand model to read the price elasticity, with checks for multicollinearity and extrapolation. The first lab is free.
Lessons
- Scatter Plots & Correlation: Is There a Linear Relationship?Free
- Simple Linear Regression by Hand: Least Squares, R² & Standard Error Pro
- Is the Slope Real? t Statistic, p-Value & Confidence Interval Pro
- Predicting a New Store: Point Forecast & Prediction Interval Pro
- Multiple Regression with LINEST: Three Drivers at Once Pro
- Dummy Variables: Regions and Seasons in a Regression Pro
- Residual Analysis: Residual Plot, Standardised Residuals & Outliers Pro
- Log Models & Elasticity, plus Two Classic Pitfalls Pro