Standardized coefficients & Multiple Linear Regression in R Rstudio Influence Tutorial Data Science

Variable importance in Linear Regression? how to measure the impact of variables in the outcome? standard coefficients?
- Which variables have more impact in the outcome??
- What is standardization?? how to apply it?
- How to identify a normal curve
- How to predict in linear regression
- How to transform back my features
- Preparing data for fitting a model
- Split data intro train and test data
- Build the model with functions
- Check models performance with Caret Package
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- What is linearity? Normality? Equality of variance? Homoscedasticity?
- Identify outliers, high influence values, cook distance?
- Residuals and their relationship with fitted or predicted values?
- What is coefficient of determination? mean squared error? R2
- overfitting and leverage
Any comment or suggestion is welcome
Contact: [e-mail]
Twitter : / raulvaleriom
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#Diagnostic #Assumptions #Normality #Homokedasticity #Variance

[@RVStats_ENG]

Test Multiple Linear Regression Assumptions in R Rstudio Check Diagnostic: ua-cam.com/video/lIHebs8ODcg/v-deo.html

[@empowercode]

Hey, great video! Particularly, I like how clear and detailed your explanations are as well as the depth of knowledge you have surrounding ML. Since I run a tech education channel as well, I love to see fellow content creators sharing, educating, and inspiring a large global audience. Keep up the great work!

[@RVStats_ENG]

Thanks for your great comment and inspiring words. Best regards :)