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What If Analysis

Regression Model Using Microsoft Excel

by Kardi Teknomo

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This tutorial is an introduction to regression model using MS Excel. You will learn how to model you data, find the best-fit model and use graph, functions and Add Ins wizard in MS excel to automate the regression. You will also learn how to solve regression using generalized inverse matrix. You may download the spreadsheet example of this tutorial here.

Using Microsoft Excel, you have at least five methods to compute linear regression

Using Excel function
Using Data Analysis Add Ins
Using MS Excel Graph trend Analysis
Using MS Excel matrix function
Using MS Excel Spreadsheet for manual computation

Excel function is very handy. If your data change dynamically, the result of regression will change immediately. Data analysis has advantage to compute the statistical criteria such as R square, ANOVA and t statistics plus probability plots of outlier. Excel Graph trend analysis is very good for plotting the graph of linear and several non-linear models (exponential, logarithm, power and polynomial), the update is also dynamic according to your data change.

Using matrix formulation and MS excel matrix function you may learn how to compute regression in matrix model. Together with using spreadsheet for manual computation, both methods have educational advantage to explain the formula of regression.

Click any topics below to enter the tutorial:

What is regression model?
How can we be sure that the best line is linear?
Hand Calculation Example of Linear Regression
Using MS Excel Function for Linear Regression Analysis
Using MS Excel Data Analysis Add-Ins for Linear Regression
Using MS Excel Graph Trend Analysis
Generalizes Inverse Matrix to Solve Regression Problem
Ordinary Least Square Method

See also: Data analysis from Questionnaire, Learning from Data, Kernel regression, Nonlinear Transformation

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Preferable reference for this tutorial is

Teknomo, Kardi. Regression Model using Microsoft Excel. http:\\people.revoledu.com\kardi\ tutorial\Regression\


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