Exam 2 R Notebook

Name: Oscar Alexander Tobar

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Exam 2

Question 5 Reads

Consider the following vectors representing the number of field goals made and attempted by a basketball player in five games:

Field Goals Made: c(18, 7, 6, 9, 10,13) Field Goals Attempted: c(36, 23, 12, 18, 24,22)

Calculate the field goal percentage for each game and select the correct average field goal percentage for the five games.

# Vectors
fg_made <- c(18, 7, 6, 9, 10, 13)
fg_made

[1] 18  7  6  9 10 13

fg_attempted <- c(36, 23, 12, 18, 24, 22)
fg_attempted

[1] 36 23 12 18 24 22

# Field goal percentage per game
fg_percentages <- (fg_made / fg_attempted) * 100

# Average field goal percentage across the six games
average_fg_percentage <- mean(fg_percentages)

# Output the result
fg_percentages

[1] 50.00000 30.43478 50.00000 50.00000 41.66667 59.09091

average_fg_percentage

[1] 46.86539

Question 6 reads:

Consider the following vectors representing the number of three-pointers made and attempted by a basketball player in five games:

Three-Pointers Made: c(3, 5,0, 6, 3, 7) Three-Pointers Attempted: c(9, 10, 8,12, 11, 12)

Calculate the three-point shooting percentage for each game and select the correct average three-point shooting percentage for the five games.

# Vectors
three_made <- c(3, 5, 0, 6, 3, 7)
three_attempted <- c(9, 10, 8, 12, 11, 12)

# Three-point percentage per game
three_point_percentages <- (three_made / three_attempted) * 100

# Average three-point percentage across the six games
average_three_point_percentage <- mean(three_point_percentages)

# Output the results
three_point_percentages

[1] 33.33333 50.00000  0.00000 50.00000 27.27273 58.33333

average_three_point_percentage

[1] 36.4899

Question 7:

Consider the following dataset representing the performance of baseball players in a season. It includes the following variables: PlayerID, Hits, At-Bats, Home Runs (HR), Walks (BB), and Strikeouts (SO).

PlayerID Hits At-Bats HR BB SO

1             112       400           25          50     60

2             124       450           22          60     65

3             121       380           8            19     67

4             106       500           20         150     92

5             140       402           11          55     70

Compute the on-base percentage (OBP) for each player and select the player with the highest OBP.

1. Player 1 b) Player 2 c) Player 3 d) Player 4 e) Player 5

To calculate OBP, you can use the following formula:

OBP = (Hits + Walks) / (At-Bats + Walks)

# Create the dataset
player_data <- data.frame(
  PlayerID = c(1, 2, 3, 4, 5),
  Hits = c(112, 124, 121, 106, 140),
  At_Bats = c(400, 450, 380, 500, 402),
  Walks = c(50, 60, 19, 150, 55)
)

# Calculate OBP
player_data$OBP <- (player_data$Hits + player_data$Walks) / 
                   (player_data$At_Bats + player_data$Walks)

# View the dataset with OBP
print(player_data)

# Identify the player with the highest OBP
max_obp_player <- player_data[which.max(player_data$OBP), ]
print(max_obp_player)