Denise Lau is an avid football fan and religiously follows every game of the National Football League. During the 2017 season, she meticulously keeps a record of how each quarterback has played throughout the season. Denise is making a presentation at the local NFL fan club about these quarterbacks. The accompanying data file contains the data that Denise has recorded, with the following variables: the player's name (Player), team's name (Team), completed passes (Comp), attempted passes (Att), completion percentage (Pct), total yards thrown (Yds), average yards per attempt (Avg), yards thrown per game (Yds/G), number of touchdowns (TD), and number of interceptions (Int). Denise feels that, for her presentation, it would remove some biases if the player names and team names are suppressed. Remove these variables from the data set.
a. Denise wants to remove outlier cases where the players have less than 5 touchdowns or more than 20 interceptions. Remove these observations from the data set.
How many observations were removed from the data?
b. Return to the original data set. Use the imputation strategy to handle missing values. If there are missing values for TD or Int, impute the missing values using the median of the variable. What are the average values of TD and Int after imputation?
Note: Round your answers to four decimal places.
Average value of TD after imputation
Average value of Int after imputation
