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This image accompanies the article, "What is the difference between Simple Linear Regression (SLR) and General Linear Model (GLM)?," which explains the difference between Simple Linear Regression (SLR) and General Linear Model (GLM). In Simple Linear Regression, the predictors are usually just the explanatory variables, and the relationship between the predictors and the response is assessed by a line (slope) and a y-intercept. In General Linear Model, the predictors may include multiple varia

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Question: What is the difference between Simple Linear Regression (SLR) and General Linear Model (GLM)?

Asked by jaswinder

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Simple linear regression (SLR) is an analysis of a set of data points with one independent variable and one dependent variable. It involves fitting a straight line through the data points with the goal of predicting the value of the dependent variable from the independent variable. General Linear Model (GLM) is a more general approach to modelling data. It is used to describe and analyze relationships between a response variable and one or more predictor variables. It involves fitting linear equations through the data points with the goal of predicting the value of the response variable from the predictor variables. GLM also allows for more than one independent and dependent variable, and can also use more complex models such as polynomial, interaction and categorical models.

Answered by text-davinci-003

Jan. 17, 2023, 7:28 p.m.

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This article was generated in part by one of OpenAI’s large-scale language-generation model, answering user jaswinder's question. Images were generated with OpenAI's AI model, DALL·E 2. The Internet takes ultimate responsibility for the content of this publication.
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Published: Tuesday, January 17, 2023

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