can you please do the following in R studio

National Football League. Consider the National Football league data. y: Games won, x$1$:Rushing yards, x$2$: Passing yards, x$3$: Punting average, x$4$: Field goal percentage, x$5$: Turnover differential, x$6$: Penalty yards, x$7$: Percent rushing, x$8$: Opponents$$ rushing yards, x$9$: Opponents$$ passing yards

$1.$ Apply the all$-$possible$-$regression procedures. Show the results of best subset regression models $($i$.$e$.$ the chosen models for a certain number of explanatory variables$).(3$ points$)$

$2.$ Use the forward selection algorithm with AIC to select a regression model $(3$ points$)$

$3.$ Use the backward selection algorithm with AIC to select a regression model $(3$ points$)$

$4.$ Use stepwise regression with AIC to select a regression model $(3$ points$)$

$5.$ Comment on the final model chosen by these procedures $(3$ points$)$

Home Ownership Status. A study was conducted attempting to relate home ownership to family income. Twenty household were selected and family income was estimated, along with information concerning home ownership $($y$=1$ indicates yes and y$=0$ indicates no$).$

$6.$ Fit a logistic regression model to the response variable y$.(3$ points$)$

$7.$ Does the model deviance indicate that the logistic regression model is adequate? $(3$ points$)$

$8.$ Show the residual plots for the model. $(3$ points$)$

$9.$ Provide an interpretation of the parameter $\backslash$beta $1$ in this model. $(3$ points$)$

$10.$ Expand the linear predictor to include a quadratic term in income $($i$.$e$.$ add x$2$ as another explanatory variable$).$ Is there any evidence that this quadratic term is required in the model? $(3$ points$)$