Question $2$: Perform linear regression model on the bike sharing data set from Question $2.$

a$.$ Provide the summary result of the regression model with "casual" as the response variable and "temp", "hum" as the predictors.

b$.$ What other predictors do you think might be important for the modelling of the variable "casual"? Please construct another linear model including more predictors and provide the summary result of the second model.

c$.$ Perform $1000$ times of $5-$fold cross validation and each time you randomly partition the dataset into five equal parts. You will use $80\%$ of the data as the training data and $20\%$ as the validating data. For models in a$)$ and b$),$ calculate the total sum of squared prediction error divided by the size of the validation data and by the number of cross$-$validations. Which model has better predictive power?

Wirte in R language pls