Regression in R
R
How to Interpret glm Output in R (With Example)
The glm() function in R can be used to fit generalized linear models.
This function uses the following syntax:
glm(formula, family=gaussian, data, …)
where:
formula: The formula for...
R
How to Calculate BIC in R
The Bayesian Information Criterion, often abbreviated BIC, is a metric that is used to compare the goodness of fit of different regression models.
In practice,...
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How to Calculate AIC in R (Including Examples)
The Akaike information criterion (AIC) is a metric that is used to compare the fit of several regression models.
It is calculated as:
AIC = 2K...
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How to Calculate Mallows’ Cp in R
In regression analysis, Mallows’ Cp is a metric that is used to pick the best regression model among several potential models.
We can identify the...
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How to Interpret Pr(>|t|) in Regression Model Output in R
Whenever you perform linear regression in R, the output of your regression model will be displayed in the following format:
Coefficients:
...
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How to Plot a Polynomial Regression Curve in R
Polynomial regression is a regression technique we use when the relationship between a predictor variable and a response variable is nonlinear.
This tutorial explains how...
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How to Interpret Diagnostic Plots in R
Linear regression models are used to describe the relationship between one or more predictor variables and a response variable.
However, once we’ve fit a regression...
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