Test Multiple Linear Regression Assumptions in R Rstudio Check Diagnostic | Tutorial Data Science

Are Linear Model assumptions met? How to test and check Multiple Linear Regression analysis?
We'll discuss and answer various questions:
- Preparing data for fitting a model
- Split data intro train and test data
- Build the model with functions
- Check models performance with Caret Package
- 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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#Learn #Rstudio #R #Regression #Linear python from zero #beginner #Learning
Statistical analysis ## Factor, vector, list, jupyter, notebook
input and output # data mining #Machine learning and supervised learning
#Diagnostic #Assumptions #Normality #Homokedasticity #Variance

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* Standardized coefficients & Multiple Linear Regression in R Rstudio Influence: ua-cam.com/video/rVFLoVcZ9jA/v-deo.html
* Random Walk and Time Series Tutorial in R: ACF Dickey Fuller Test Ljung Box stationarity ua-cam.com/video/PjdKg5kaxXA/v-deo.html

[@REAPER7777]

Can you please share the script?