Math 455 – Statistics

After typing/cutting and pasting each command, explain in a sentence or two what the command is actually doing You may include a graph, etc. if appropriate. For example, the first command is importing the data into r. (Your first command will be different as you will have saved the file to a different location, initially.)

Ch08_Roller_coaster <- read.csv("/Volumes/LBARTON/2013 -2014/Statistics/r/Data sets from Stats textbook/Ch08_Roller_coaster.csv")

View(Ch08_Roller_coaster)

This command…..

plot(Ch08_Roller_coaster$Drop,Ch08_Roller_coaster$Duration)

This command…..

plot(Ch08_Roller_coaster$Drop,Ch08_Roller_coaster$Duration,xlab="Drop in feet",ylab="Duration in seconds",main="Roller Coaster")

This command…..

lm(Ch08_Roller_coaster$Duration~Ch08_Roller_coaster$Drop)

This command…..

abline(lm(Ch08_Roller_coaster$Duration~Ch08_Roller_coaster$Drop),col="blue")

This command….

regdrop=lm(Ch08_Roller_coaster$Duration~Ch08_Roller_coaster$Drop)

This command…..

regdrop

This command…..

summary(regdrop)

This command…..

data.frame(Ch08_Roller_coaster$Duration,Ch08_Roller_coaster$Drop,fitted.value=fitted(lm(Ch08_Roller_coaster$Duration~Ch08_Roller_coaster$Drop)),residual=resid(lm(Ch08_Roller_coaster$Duration~Ch08_Roller_coaster$Drop)))

This command…..

fitdrop=fitted(regdrop)

This command…..

residdrop=resid(regdrop)

This command…..

plot(fitdrop,residdrop)

This command…..

plot(fitdrop,residdrop,xlab="fitted duration",ylab="residual")

This command…..

abline(0,0)

This command…..

Attendance 2006

The data below provides information about various baseball teams in 2006, their number of wins and home game attendance.

Team / Wins / Runs / Home Attendance
Minnesota Twins / 96 / 801 / 28210
New York Yankees / 97 / 930 / 51858
Toronto Blue Jays / 87 / 809 / 28422
Cleveland Indians / 78 / 870 / 24667
Chicago White Sox / 90 / 868 / 36511
Texas Rangers / 80 / 835 / 29490
Baltimore Orioles / 70 / 768 / 26583
Los Angeles Angels / 89 / 766 / 42059
Detroit Tigers / 95 / 822 / 32048
Seattle Mariners / 78 / 756 / 30626
Kansas City Royals / 62 / 757 / 17158
Boston Red Sox / 86 / 820 / 36182
Oakland Athletics / 93 / 771 / 24402
Tampa Bay Devil Rays / 61 / 689 / 16901
  1. Create a scatterplot of “Home Attendance” (y) vs. “wins” (x)
  2. Create and display the LSRL
  3. Create a residual plot (predicted values on the x – axis and residuals on the y-axis.
  4. Draw the line y = 0 on your residual plot.
  5. Display the regression analysis.
  6. Based upon your work thus far, do you think a linear model is appropriate here? Explain.
  7. Interpret the meaning of the slope.
  8. Interpret the meaning of
  9. On your residual graph, the point in the upper right represents the Yankees. What can you say about the residual for the Yankees?
  10. What is the correlation between wins and average attendance?
  11. What would you predict about the average attendance for a team that is 2 standard deviations about the average in wins?
  12. If a team is 1 standard deviation below average in attendance, what would you predict about the number of games the team has won?

Homework: page 192 – 195 # 5, 7, 16, 17, 22, 34