Satisfaction Enjoyment Recommend Type SpendingLastYear SpendingThisYear BirthDate Satisfied High Neutral Action 379 661 7/30/1992 Very Satisfied High Will Role Play 400 320 10/17/1984 Satisfied Neutral Neutral Action 324 625 9/22/1985 Satisfied High Will Role Play 452 150 1/7/1988 Neutral Very High Definitely Will Sports 398 716 11/18/1991 Neutral Very High Neutral Action 168 555 9/6/1994 Neutral Very High Will Sports 203 519 11/26/1985 Neutral High Neutral Sports 252 259 7/14/1984 Neutral High Will Sports 217 475 4/1/1996 Satisfied High Neutral Action 288 140 9/26/1983 Satisfied Very High Will Action 429 432 10/5/1986 Very Satisfied Very High Definitely Will Role Play 190 166 2/26/1996 Satisfied High Neutral Sports 161 237 3/14/1992 Neutral Very High Definitely Will Action 406 190 10/7/1987 Satisfied Very High Will Role Play 426 726 11/6/1986 Satisfied Very High Neutral Action 436 125 2/4/1990 Satisfied High Neutral Action 347 368 9/17/1985 Satisfied Very High Definitely Will Sports 482 677 5/23/1997 Dissati

1. Count the number of players who play action games. What percentage of players play action games? Note: In Excel, use the COUNTIF function to count the number of players. 2. Sort the data only by total spending on games this year in descending order. How much did the first player spend in the ordered list the most this year? Note: In Excel, use the Data>Sort&Filter>Sort to to sort the data. 3. Are there any missing values in the dataset? If there are missing values, which variables have missing values? How many missing values are there in the data set?4. First use the omission strategy to handle missing values. How many observations are removed due to missing values? 5. Second, return to the original data. Use the imputation strategy to handle missing values. If there are missing values for SpendingLastYear and SpendingThisYear, use the imputation strategy to replace the missing values with the median of the variable. What are the average values of these variables after imputation?6. Bin the total spending on games last year into four equal size groups. Label the groups using numbers 1 (lowest values) to 4 (highest values). How many customers are assigned to group 4. 7. Bin the total spending on games this year into following three groups: <250, between 250 and 500, and >500. Label the groups using numbers 1 (lowest values) to 3 (highest values). How many observations are assigned to group 2? Note: In Excel, use the VLOOKUP function to bin the data. 8. Create a new variable called Difference that contains the difference between this years and last years spending on games for the players. What is the average difference? 9. Create a new variable called PercentDifference that contains the percent difference between this years and last years spending on games for players. Use the following formula: ((SpendingThisY ear Spending LastY ear) / SpendingLastY ear) * 100 What is the average percent difference?10. Create a new variable Age that contains the players ages as of January 1, 2020. What is the average age of the players? Note: In Excel, use first the YEARFRAC function to calculate the difference in years between two dates, next use the INT function to display the integer value of the difference in years. 11. The variable Satisfaction contains five ordered categories; Very Dissatisfied, Dissatisfied, Neutral, Satisfied, and Very Satisfied. Replace the category names with scores ranging from 1 (Very Dissatisfied) to 5 (Very Satisfied). What Is the average satisfaction score? Note: In Excel, use the IF function to create five ordered categories. 12. The variable Type contains three unordered game categories: Action, Role Play, and Sports. To facilitate subsequent analyses, transform type into dummy variables. Use the least frequent category as the reference category. Which category is the reference category? How many dummy variables should be created? Note: In Excel, use the COUNTIF function to count the number of players in each category.