The data sets for the case studies used in the book, along with some scripts used for illustration, can be downloaded from http://support.sas.com/downloads/package.htm?pid=1817. Note that some data sets are in the JMP Sample Data Library. Course materials developed by two professors are attached below. Eratta, which will be addressed in the next edition, are listed here as well.
Links to useful resources:
A collection of add-ins used for data mining and predictive modeling, including add-ins for setting the random seed and changing the cutoff value for classification for a confusion matrix (note that both of these add-ins are referred to in the book):
Jim Grayson taught a graduate level course at Georgia Regents University (summer 2015), Business Analytics for Managers, prior to the release of this book. His course materials, including his schedule and syllabus, are attached. The course used some examples from Business Statistics, 3e (Sharpe, DeVeaux and Velleman). However, Jim uses a good deal of content from Building Better Models (Chapter 3), and the materials for the modeling chapters (Chapters 4-6, and part of Chapters 8 and 9) are based on Building Better Models.
Bob Nydick is teaching a graduate level online course at Villanova University (fall 2015), Analytical Methods for Data Mining, using this book. Bob has shared materials he has developed for the course (not including Multiple Regression and Logistic Regression). Thanks Bob!
Do you have materials or resources for this book or a similar course, or for specific topics covered in the book, that you'd be willing to share? Please consider posting on the Academic Community. Or, we'd be happy to post on your behalf.
We hope you enjoy this book! Questions, comments and suggestions? Please use the "Add a comment" button at the bottom of this page.
Instructor solutions are under development. To request instructor access to exercise solutions, please contact mia.stephens.
Figure 4.24 - needs to be retaken with Log(Bal_Total) instead of Bal_Total.
Figures 4.26 and 4.27 need to be retaken with AccountAge.
Page 88 - change "11 remaining" to "12 remaining"
Chapter 5, remove Exercise 5.7
Figure 6.10 is incorrect. It should be:
Figure 6.12 is incorrect. It should be (the one shown is after 6 splits):
Bottom of page 158 - last sentence, missing parenthesis. It should read, "... has 15 splits (see Figure 6.26). Note..."
Figure 7.22: Add a note on page 202, results will be slightly different on a Mac (using the same random seed).
Figure 7.33 and 7.34: The output will be slightly different on a Mac (using the random seed of 1000).
Page 218, Exercise 7.1. Should be changed to: In the example, we fit a neural network with one layer and three notes, all using the TanH activation function.
a. Fit the model described in Example 1, and also fit a model with one layer with three nodes, using TanH, linear, and Gaussian activation functions.
Page 232, first sentence in the example should read:
"...to illustrate how cross-validation is used in building predictive models."
Page 234: Add the following sentence, "Note: Rows are randomly assigned to the training, validation and test sets. So, your validation column will likely be different than what is shown here. Use Boston Housing BBM Ch8 with Validation.jmp to produce the results shown in the remainder of this chapter."
Page 251 and 252, exercise 8.1 and 8.2: the data set is Boston Housing BBM Ch8.jmp.
Page 253, exercise 8.5: The Credit Card Marketing BBM.jmp data is described in Example 1 in Chapter 6.
Figure 9.6 - the caption should read "Boosted Tree Prediction formula for Prob[Survived=Yes]"
Note: On 12/7/2015 an updated version of the data sets was uploaded to the SAS textbook page. The following changes were made:
The missing value column property was removed from the CreditRiskModeling BBM.jmp data table (used in Chapter 7).
The CreditRiskModeling BBM Clean.jmp was added. This file has been prepared for modeling (see page 211).