| Finding descriptive statistics |
nutrient.csv
nutrient.sas |
1.4 - Example |
| Finding generalized variance |
nutrient3.sas
DETERMAT.mac |
1.6 - Example: Women's Nutrition Data |
| Creating plots of the bivariate normal distribution |
normplot.sas
phi_equation_r=0.7.txt |
4.2 - Example: Bivariate Normal Distribution |
| Calculating Mahalonobis distances |
mahalonobis.sas |
4.3 - Exponent of Multivariate Normal Distribution |
| Producing QQ plots |
Q_Qplot.sas |
4.4 - Multivariate Normality and Outliers |
| Producing a covariance matrix for a dataset |
wechsler.sas
wechsler.csv |
4.7 - Example: Wechsler Adult Intelligence Scale |
| Plotting a 95% confidence ellipse corresponding to a specified variance-covariance matrix |
ellplot.sas |
4.9 - Special Cases: p = 2 |
| Generate confidence intervals for population means |
CI_pop_means.sas |
5.2 - Interval Estimate of Population Mean |
| Partial correlation |
wechsler2.sas |
6.2 - Example: Wechsler Adult Intelligence Scale |
| Hotelling's \(T^{2}\) test |
nutrient4.sas
nutrient.csv |
7.1.4 - Example: Women’s Nutrition Data and Associated Confidence Intervals |
| Simultaneous confidence intervals |
nutrient5.sas |
7.1.4 - Example: Women’s Nutrition Data (Simultaneous Confidence Intervals) |
| Profile plots |
nutrient6.sas |
7.1.5 - Profile Plots |
| Paired Hotelling's \(T^{2}\) test |
spouse.sas
spouse.csv |
7.1.9 - Example: Spouse Data |
| Simultaneous Bonferroni Confidence intervals |
spouse1a.sas |
7.1.10 - Confidence Intervals |
| Paired Hotelling's \(T^{2}\) test: Matching Perceptions |
spouse2.sas |
7.1.11 - Question 2: Matching Perceptions |
| 2 Sample Hotelling's \(T^{2}\) test |
swiss10.sas
swiss3.csv
|
7.1.15 - The Two-Sample Hotelling's T-Square Test Statistic |
| Check for Normality |
potterya.sas
pottery.txt |
8.4 - Example: Pottery Data - Checking Model Assumptions |
| MANOVA |
pottery.sas |
8.5 - Example: MANOVA of Pottery Data |
| Split-Plot Analysis |
dog2.sas
dog1.txt |
9.2 - An Example |
| Repeated Measures |
dog.sas |
9.4 - Approach 2 - MANOVA |
| Mixed Model Analysis |
dog3.sas |
9.7 - Approach 3 - Mixed Model Analysis |
| Test for homogeneity of the variance-covariance matrices using Bartlett's test |
insect.sas
insect.csv |
10.4 - Example: Insect Data |
| Bartlett's test to check for homogeneity of the variance-covariance matrices |
swiss9.sas
swiss1.csv |
10.7 - Example: Swiss Bank Notes |
| Principal component procedures |
places.sas
places.csv |
11.3 - Example: Places Rated |
| Principal component procedures using the standardized data |
places1.sas |
11.6 - Example: Places Rated after Standardization |
| Factor Analysis |
places2.sas |
12.4 - Example: Places Rated Data - Principal Component Method |
| Factor Analysis - Maximum Likelihood method |
places3.sas |
12.8 - Example: Places Rated Data |
| Canonical Correlation Analysis |
sales.sas
sales.csv |
13.2 - Example: Sales Data |
| Cluster Analysis - Complete Linkage |
wood1.sas
wood.csv |
14.5 - Agglomerative Method Example |
| Cluster Analysis - Ward's Method |
wood5.sas |
14.7 - Ward’s Method |
| Cluster Analysis - K-Means |
wood6.sas |
14.9 - Defining Initial Clusters |