Project #2
STAT 875
Fall 2012
Complete the following problems below. Within each part, include your R program output with code
inside of it and any additional information needed to explain your answer. Note that you will need to
edit your output and code in order to make it look nice after you copy and paste it into your Word
document.
1) (27 total points) Continue using taste as the response variable and acetic acid as the predictor
variable as in project #1 for the cheese data. Complete the following.
a) (2 points) Give the ANOVA table.
b) (3 points) Using the relevant information from the ANOVA table, perform an F-test for 1 = 0
vs. 1  0. Use  = 0.05.
c) (3 points) What is R2 for the sample regression model? Fully interpret its value.
d) (8 points) Using my examine.mod.simple() function, comment on the following items with
regards to the model:
i) Linearity of the regression function
ii) Constant error variance
iii) Normality of i
iv) Outliers
Make sure to specifically refer to plots and numerical values in your comments.
e) (6 points) You should detect one or more potential problems with the model through the work
in part Error! Reference source not found.. Transform the response variable to be taste .
Why do you think this transformation was chosen? Determine if the transformation helps to
solve a problem with the model.
f) (3 points) Using the new model that was estimated for part Error! Reference source not
found., find the 95% confidence intervals for taste (not taste ) when acetic acid has a value
of 4.5 and 6.4. Compare the intervals to those found in project #1. Which intervals (project #1
or #2) are more likely to have 95% confidence? Explain.
g) (2 points) Are there any other problems remaining the model after what was done in part
Error! Reference source not found.? Justify your answer. Note that you do not need to
actually implement any changes to the model.
2) (12 total points) The extra credit of project #1 asked you to simulate data from a sample
regression model using taste as the response variable (not transformed) and acetic acid as the
predictor variable. Complete the following using my simulated data from the answer key.
a) (1 point) Run my code to simulate the data. Give the simulated Y values to show that you
simulated the data correctly.
b) (8 points) Estimate the appropriate regression model for the simulated data. Using my
examine.mod.simple() function, comment on the following items with regards to the model:
i) Linearity of the regression function
ii) Constant error variance (do not examine the Box-Cox transformation value)
iii) Normality of i
iv) Outliers
Make sure to specifically refer to plots and numerical values in your comments.
c) (3 points) Answer one of the following:
i) If you found potential problems, what could be a reason for them?
1
ii) If you did not find potential problems, why is this expected?
2