R Notebook

# Read in the data
NBA = read.csv("NBA_train.csv")
str(NBA)

# How many wins to make the playoffs?
table(NBA$W, NBA$Playoffs)

# Compute Points Difference
NBA$PTSdiff = NBA$PTS - NBA$oppPTS

# Check for linear relationship
plot(NBA$PTSdiff, NBA$W)

# Linear regression model for wins
WinsReg = lm(W ~ PTSdiff, data=NBA)
summary(WinsReg)

# VIDEO 3

# Linear regression model for points scored
PointsReg = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + DRB + TOV + STL + BLK, data=NBA)
summary(PointsReg)

# Sum of Squared Errors
PointsReg$residuals

SSE = sum(PointsReg$residuals^2)
SSE

# Root mean squared error
RMSE = sqrt(SSE/nrow(NBA))
RMSE

# Average number of points in a season
mean(NBA$PTS)

# Remove insignifcant variables
summary(PointsReg)

PointsReg2 = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + DRB + STL + BLK, data=NBA)
summary(PointsReg2)

PointsReg3 = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + STL + BLK, data=NBA)
summary(PointsReg3)

PointsReg4 = lm(PTS ~ X2PA + X3PA + FTA + AST + ORB + STL, data=NBA)
summary(PointsReg4)

# Compute SSE and RMSE for new model
SSE_4 = sum(PointsReg4$residuals^2)
RMSE_4 = sqrt(SSE_4/nrow(NBA))
SSE_4

RMSE_4

 #VIDEO 4

# Read in test set
NBA_test = read.csv("NBA_test.csv")

# Make predictions on test set
PointsPredictions = predict(PointsReg4, newdata=NBA_test)

# Compute out-of-sample R^2
SSE = sum((PointsPredictions - NBA_test$PTS)^2)
SST = sum((mean(NBA$PTS) - NBA_test$PTS)^2)
R2 = 1 - SSE/SST
R2

# Compute the RMSE
RMSE = sqrt(SSE/nrow(NBA_test))
RMSE 

Question to be answered in this activity

Consider the following vectors representing the number of three-pointers made and attempted by a basketball player in five games: Three-Pointers Made: c(4, 5, 3, 6, 7) Three-Pointers Attempted: c(9, 10, 8, 11, 12) Calculate the three-point shooting percentage for each game and select the correct average three-point shooting percentage for the five games.

# Step 1: Define the vectors
made <- c(4, 5, 3, 6, 7)
attempted <- c(9, 10, 8, 11, 12)

# Step 2: Calculate the shooting percentage for each game
percentages <- made / attempted * 100

# Step 3: Print the percentages for each game
percentages

[1] 44.44444 50.00000 37.50000 54.54545 58.33333

# Step 4: Calculate the average percentage across all games
average_percentage <- mean(percentages)
average_percentage

[1] 48.96465

The three-point shooting percentage for each game is:

Game 1: 44.44%

Game 2: 50.00%

Game 3: 37.50%

Game 4: 54.55%

Game 5: 58.33%

To find the average three-point shooting percentage, we took the mean of these five individual game percentages.

The correct average three-point shooting percentage across the five games is approximately 48.96%.