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In this particular case, 60 % of the variability of the Weight is explained by the Height. The closer to 1 the R² is, the better the fit is. The R² (coefficient of determination) indicates the % of variability of the dependent variable which is explained by the explanatory variables. The first table displays the goodness of fit coefficients of the model. How to interpret the results of a simple linear regression in XLSTAT? Since the column title for the variables is already selected, leave the Variable labels option activated. In the General tab, select the "Weight" variable in the Dependent variable field and "Height" variable in the Quantitative explanatory variable.

In the ribbon, select XLSTAT > Modeling data > Linear Regression This dataset is also used in the two tutorials on multiple linear regression and ANCOVA, with the Height, Age and then Gender as explanatory variables. The Linear Regression method belongs to a larger family of models called GLM (Generalized Linear Models), as does the ANOVA. Here, the dependent variable is the weight, and the explanatory variable is height.

Using simple linear regression, we want to find out how the weight of the children varies with their height, and to verify if a linear model makes sense. They concern 237 children, described by their gender, age in months, height in inches (1 inch = 2.54 cm), and weight in pounds (1 pound = 0.45 kg). Introduction to Experimental Ecology, New York: Academic Press, Inc. How to run simple linear regression in XLSTAT? Dataset for running a linear regression If you are trying to predict a variable depending on several others, do not hesitate to read our tutorial on Multiple Linear Regression.

Simple linear regression enables you to predict a variable depending on another variable, on the basis of a linear relationship inferred by a supervised learning algorithm. Not sure this is the modeling feature you are looking for? Check out this guide. Simple linear regression is based on Ordinary Least Squares (OLS). This tutorial will help you set up and interpret a simple linear regression in Excel using the XLSTAT software.