Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 16: Restructuring SAS Data Sets
Using Arrays
A. Introduction
Arrays can be used to restructure data
PROC TRANSPOSE also provides this feature but using arrays in a
D

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 9: Multiple Regression Analysis
A. Introduction
The dependent variable (the one you want to predict) must be a
continuous variable (except for logistic regression whe

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 15: Working with Arrays
A. Introduction
Arrays can reduce the amount of coding in a SAS DATA step
They shorten a program that repeats one or more lines of code with

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 11: Psychometrics
A. Introduction
Perform a test
Perform item analysis
Test reliability (Cronbachs Alpha)
Test interrater reliability (Coefficient Kappa)
B. Using

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 14: Data Set Subsetting,
Concatenating, Merging, and Updating
A. Introduction
Subsetting data
Combining data
B. Subsetting
The SET statement reads observations from

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 10: Factor Analysis
B. Types of Factor Analysis
There are two types of factor analysis
Exploratory
Two basic approaches
Principal components analysis
Factor analysis

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 8: Repeated Measures Designs
A. Introduction
Repeated means any factor where each subject is measured at every
level for that factor.
REPEATED statement can be added

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 12: SAS INPUT Statement
B. List Input
SAS can read data values separated by one or more spaces
Must read every variable on a line
Data values must be separated by o

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 13: External Files
A. Introduction
Simple ASCII files are read with INFILE and INPUT
SAS data sets use two-level SAS data set names and do not require
INPUT statemen

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 7: Analysis of Variance
B. One-Way Analysis of Variance
When you have more than two groups to compare we use ANOVA
(analysis-of-variance)
The advantage is that we are

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 3: Analyzing Categorical Data
A. Introduction
In this chapter we look at methods for analyzing data that represent
categories rather than numerical values such as gen

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 1
A. Starting Out with SAS
The key objective is to get one program to run successfully
Branch out and your expertise will grow
If you are running on a mainframe then

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 4: Working with Date and
Longitudinal Data
A. Introduction
Longitudinal data is data collected for the same set of subjects at
different times.
B. Processing Date Var

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 5: Correlation and Simple
Regression
A. Introduction
Pearson correlation coefficient measures the strength of a linear
relationship between two variables.
Ranges from

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 6: T-tests and Nonparametric
Comparisons
A. Introduction
T-test is appropriate when:
2 groups must be independent
Sampling means are normally distributed
Variances fo

Applied Statistics and the SAS
Programming Language
ISM 4930/6930
Dr. A. Makris
Chapter 2: Describing Data
A. Assessing Normality
Besides mean, sum, frequency we use histograms, stem-and-leaf
plots, test for normality of distributions, and a variety of o