The nbaallelo$\_$mlr$.$csv data base contains information on $126315$ NBA games between $1947$ and $2015.$ The columns report the points made by one team, the Elo rating of that team coming into the game, the Elo rating of the team after the game, whether the team won or lost, and the points made by the opposing team.

Load the data set into a data frame.

Recode the categorical variable game$\_$result into a dummy variable, win.

Use the ols function to perform a multiple regression with pts as the response variable and elo$\_$i$,$ win, and opp$\_$pts$,$ in that order, as the predictor variables

Create an analysis of variance table using the results of the multiple regression.

Ex: If the Elo rating of the team after the game, elo$\_$n$,$ is used instead of elo$\_$i$,$ the output is:

sum$\_$sq df F PR$(>$F$)$

elo$\_$n $1\mathrm{.}384812$e$+051\mathrm{.}02440\mathrm{.}0294400\mathrm{.}0$

game$\_$result$\_$W $9\mathrm{.}340871$e$+061\mathrm{.}0164585\mathrm{.}4711210\mathrm{.}0$

opp$\_$pts $1\mathrm{.}689391$e$+071\mathrm{.}0297669\mathrm{.}3872140\mathrm{.}0$

Residual $7\mathrm{.}168588$e$+06126310\mathrm{.}0$ NaN NaN