# Questions tagged [linear-regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

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### How to interpret Variance Inflation Factor (VIF) results?

From various books and blog posts, I understood that the Variance Inflation Factor (VIF) is used to calculate collinearity. They say that VIF till 10 is good. But I have a question. As we can see in ...
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### Correlation vs Multicollinearity

I have been taught to check correlation matrix before going for any algorithm. I have a few questions around the same: Pearson Correlation is for numerical variables only. What if we have to check ...
• 161
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### Confidence interval interpretation in linear regression when errors are not normally distributed

I've read that "If the error distribution is significantly non-normal, confidence intervals may be too wide or too narrow" (source). So, can anyone elaborate on this? When are the confidence intervals ...
• 143
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### Assumptions of linear regression

In simple terms, what are the assumptions of Linear Regression? I just want to know that when I can apply a linear regression model to our dataset.
• 119
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### Linear Regression and scaling of data

The following plot shows coefficients obtained with linear regression (with mpg as the target variable and all others as predictors). For mtcars dataset (here and ...
• 1,578
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### xgboost: Is there a way to perform regression on rates/percentages data?

I have a dependent variable, $Y$, that is made up of rates/percentages data, so each value is between $0$ and $1$. I was attracted to the xgboost library because it allows focusing in on specific ...
• 280
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### Finding optimal weights for models

I'm trying to implement an algorithm to find the minimal value of a function. Before moving to sigmoid activation functions, i'm trying to understand linear regression. Usually, a gradient descent ...
• 409