| Chapter 1
|
cereal_data.sas
- Read in the cereal data from an Excel
file, find the mean vector and
covariance matrix, and standardize the
data |
|
graph_mult_normal.sas
- Graph the bivariate normal
distribution using a 3D surface plot and
a contout plot |
|
| Chapter 2
|
| Chapter 3
|
cereal_ch3.sas
- Examples for bubble plots, 3D scatter
plots, 3D bubble plots, star plots,
Andrews' plots, and Trellis histogram
plots |
|
vnorm_ex.sas
- Shows how to generate data from a
multivariate normal distribution.
A bivariate normal distribution is given
as an example, and bivariate density
estimation is performed to verify the
results match with |
|
| Chapter 4
|
bi_norm.sas
- Examples of finding the trace,
eigenvalues, and eigenvectors of a
matrix; the bivariate normal
distribution is graphed |
|
| Chapter 5
|
| Chapter 6
|
| Chapter 7
|
placekick_ch7.sas
- Perform discriminant analysis to
classify the placekicks as successes or
failures |
|
wheat.sas
- Perform discriminant analysis to
classify the wheat kernels as Healthy,
Sprout, or Scab |
|
| Chapter 8
|
| Chapter 9
|
| Chapter 10
|
| Chapter 11
|
| Chapter 12
|