R Programming , Logistic and Linear regression, Integrals

Course details

In this class, we cover the following :

• Fundamentals of R

Assignment andArithmetic with R

Vectors, list and matrix

loops (for, if ,if else, while, repeat )

functions

• Some nice Plots for data visualization (outlier detection, correlation coefficients )
• How to detect andeliminate outliers and missing valuesfrom the data
• How to use the mallows'CP to select the best subset of parameters for the linear regression model

• logistic and linear regression models

How to use the mallows'CP to select the best subset of parameters for the linear regression model

confidence intervals of parameters

model performance , prediction and interpretation du result

• Integral approximation

By the end of this course , you will be able to effectively code in R. You will be able to summarize your data , visualize your data , detect and eliminate outliers and missing values form your data ,construct and interpret a logistic or linear regression model using the best subset of parameters,predict , approximate complex integral and more .