12/30/2023 0 Comments Statplus mac lienar regression![]() Independent variables (aka explanatory variables, or predictors) are the factors that might influence the dependent variable. Regression analysis helps you understand how the dependent variable changes when one of the independent variables varies and allows to mathematically determine which of those variables really has an impact. Technically, a regression analysis model is based on the sum of squares, which is a mathematical way to find the dispersion of data points. The goal of a model is to get the smallest possible sum of squares and draw a line that comes closest to the data. ![]() In statistics, they differentiate between a simple and multiple linear regression. Simple linear regression models the relationship between a dependent variable and one independent variables using a linear function. ![]() If you use two or more explanatory variables to predict the dependent variable, you deal with multiple linear regression. If the dependent variable is modeled as a non-linear function because the data relationships do not follow a straight line, use nonlinear regression instead. ![]() Plot this information on a chart, and the regression line will demonstrate the relationship between the independent variable (rainfall) and dependent variable (umbrella sales): The focus of this tutorial will be on a simple linear regression.Īs an example, let's take sales numbers for umbrellas for the last 24 months and find out the average monthly rainfall for the same period. ![]()
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