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Regression in Python

How to Calculate AIC of Regression Models in Python

The Akaike information criterion (AIC) is a metric that is used to compare the fit of different regression models. It is calculated as: AIC = 2K...

How to Use Pandas Get Dummies – pd.get_dummies

Often in statistics, the datasets we’re working with include categorical variables. These are variables that take on names or labels. Examples include: Marital status (“married”, “single”,...

How to Perform a Breusch-Godfrey Test in Python

One of the key assumptions in linear regression is that there is no correlation between the residuals, e.g. the residuals are independent. To test for...

Logarithmic Regression in Python (Step-by-Step)

Logarithmic regression is a type of regression used to model situations where growth or decay accelerates rapidly at first and then slows over time. For...

Exponential Regression in Python (Step-by-Step)

Exponential regression is a type of regression that can be used to model the following situations: 1. Exponential growth: Growth begins slowly and then accelerates...

How to Calculate Residual Sum of Squares in Python

A residual is the difference between an observed value and a predicted value in a regression model. It is calculated as: Residual = Observed value –...

How to Calculate Cook’s Distance in Python

Cook’s distance is used to identify influential observations in a regression model. The formula for Cook’s distance is: Di = (ri2 / p*MSE) * (hii / (1-hii)2) where: ri is the...

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