Presenting a straightforward introduction from the ground up, SAS® Essentials: Mastering SAS for Data Analytics, Second Edition illustrates SAS using hands-on learning techniques and numerous real-world examples. Keeping different experience levels in mind, the highly-qualified author team has developed the book over 20 years of teaching introductory SAS courses.
Divided into two sections, the first part of the book provides an introduction to data manipulation, statistical techniques, and the SAS programming language. The second section is designed to introduce users to statistical analysis using SAS Procedures. Featuring self-contained chapters to enhance the learning process, the Second Edition also includes:
- Programming approaches for the most up-to-date version of the SAS platform including information on how to use the SAS University Edition
- Discussions to illustrate the concepts and highlight key fundamental computational skills that are utilized by business, government, and organizations alike
- New chapters on reporting results in tables and factor analysis
- Additional information on the DATA step for data management with an emphasis on importing data from other sources, combining data sets, and data cleaning
- Updated ANOVA and regression examples as well as other data analysis techniques
- A companion website with the discussed data sets, additional code, and related PowerPoint® slides
PART I: DATA MANIPULATION AND THE SAS® PROGRAMMING LANGUAGE
1: GETTING STARTED
1.1 USING SAS IN A WINDOWS ENVIRONMENT
1.2 YOUR FIRST SAS ANALYSIS
1.3 HOW SAS WORKS
1.4 TIPS AND TRICKS FOR RUNNING SAS PROGRAMS
2: GETTING DATA INTO SAS
2.1 USING SAS DATA SETS
2.2 UNDERSTANDING SAS DATA SET STRUCTURE
2.3 RULES FOR SAS VARIABLE NAMES
2.4 UNDERSTANDING SAS VARIABLE TYPES
2.5 METHODS OF READING DATA INTO SAS
2.6 GOING DEEPER: MORE TECHNIQUES FOR ENTERING DATA
3: READING, WRITING, AND IMPORTING DATA
3.1 WORKING WITH SAS LIBRARIES AND PERMANENT DATA SETS
3.2 CREATING PERMANENT SAS DATA SETS USING THE WINDOWS FILE NAME TECHNIQUE
3.3 CREATING PERMANENT SAS DATA SETS USING AN SAS LIBRARY
3.4 CREATING A SAS LIBRARY USING A DIALOG BOX
3.5 CREATING A SAS LIBRARY USING CODE
3.6 USING DATA IN PERMANENT SAS DATA SETS
3.7 IMPORTING DATA FROM ANOTHER PROGRAM NEW VARIABLES
4.3 USING IF-THEN-ELSE CONDITIONAL STATEMENT ASSIGNMENTS
4.4 USING DROP AND KEEP TO SELECT VARIABLES
4.5 USING THE SET STATEMENT TO READ AN EXISTING DATA SET
4.6 USING PROC SORT
4.7 APPENDING AND MERGING DATA SETS
4.8 USING PROC FORMAT
4.9 GOING DEEPER: FINDING FIRST AND LAST VALUES
5: PREPARING TO USE SAS PROCEDURES
5.1 UNDERSTANDING SAS SUPPORT STATEMENTS
5.2 UNDERSTANDING PROC STATEMENT SYNTAX
5.3 USING THE ID STATEMENT IN A SAS PROCEDURE
5.4 USING THE LABEL STATEMENT IN A SAS PROCEDURE
5.5 USING THE WHERE STATEMENT IN A SAS PROCEDURE
5.6 USING PROC PRINT
5.7 GOING DEEPER: SPLITTING COLUMN TITLES IN PROC PRINT
5.8 GOING DEEPER: COMMON SYSTEM OPTIONS
6: SAS® ADVANCED PROGRAMMING TOPICS PART 1
6.1 USING SAS FUNCTIONS
6.2 USING PROC TRANSPOSE
6.3 THE SELECT STATEMENT
6.4 GOING DEEPER: CLEANING A MESSY DATA SET
7: SAS® ADVANCED PROGRAMMING TOPICS PART 2
7.1 USING SAS ARRAYS
7.2 USING DO LOOPS
7.3 USING THE RETAIN STATEMENT
7.4 USING SAS MACROS
8: CONTROLLING OUTPUT USING ODS
8.1 SPECIFYING THE ODS OUTPUT FORMAT AND DESTINATION
8.2 SPECIFYING ODS OUTPUT STYLE
8.3 USING ODS TO SELECT SPECIFIC OUTPUT TABLES FOR SAS PROCEDURES
8.4 GOING DEEPER: CAPTURING INFORMATION FROM ODS TABLES
8.5 GOING DEEPER: USING TRAFFIC LIGHTING TO HIGHLIGHT SELECTED VALUES
8.6 EXTENDED ODS FEATURES
PART II: STATISTICAL ANALYSIS USING SAS® PROCEDURES
9: EVALUATING QUANTITATIVE DATA
9.1 USING PROC MEANS
9.2 USING PROC UNIVARIATE
9.3 GOING DEEPER: ADVANCED PROC UNIVARIATE OPTIONS
10: ANALYZING COUNTS AND TABLES
10.1 USING PROC FREQ
10.2 ANALYZING ONE-WAY FREQUENCY TABLES
10.3 CREATING ONE-WAY FREQUENCY TABLES FROM SUMMARIZED DATA
10.4 ANALYZING TWO-WAY TABLES
10.5 GOING DEEPER: CALCULATING RELATIVE RISK MEASURES
10.6 GOING DEEPER: INTER-RATER RELIABILITY (KAPPA)
12.3 MULTIPLE LINEAR REGRESSION USING PROC REG
12.4 GOING DEEPER: CALCULATING PREDICTIONS
12.5 GOING DEEPER: RESIDUAL ANALYSIS
13: ANALYSIS OF VARIANCE
13.1 COMPARING THREE OR MORE MEANS USING ONE-WAY ANALYSIS OF VARIANCE
13.2 COMPARING THREE OR MORE REPEATED MEASURES
13.3 GOING DEEPER: CONTRASTS
14: ANALYSIS OF VARIANCE, PART II
14.1 ANALYSIS OF COVARIANCE
14.2 GOING DEEPER: TWO-FACTOR ANOVA USING PROC MIXED
14.3 GOING DEEPER: REPEATED MEASURES WITH A GROUPING FACTOR
15: NONPARAMETRIC ANALYSIS
15.1 COMPARING TWO INDEPENDENT SAMPLES USING NPAR1WAY
15.2 COMPARING k INDEPENDENT SAMPLES (KRUSKAL–WALLIS)
15.3 COMPARING TWO DEPENDENT (PAIRED) SAMPLES
15.4 COMPARING -DEPENDENT SAMPLES (FRIEDMAN'S TEST)
15.5 GOING DEEPER: NONPARAMETRIC MULTIPLE COMPARISONS
16: LOGISTIC REGRESSION
16.1 LOGISTIC ANALYSIS BASICS
16.2 PERFORMING A LOGISTIC ANALYSIS USING PROC LOGISTIC
16.3 USING SIMPLE LOGISTIC ANALYSIS
16.4 MULTIPLE BINARY LOGISTIC ANALYSIS
16.5 GOING DEEPER: ASSESSING A MODEL'S FIT AND PREDICTIVE ABILITY
17: FACTOR ANALYSIS
17.1 FACTOR ANALYSIS BASICS
18: CREATING CUSTOM GRAPHS
18.1 CREATING SCATTERPLOTS AND LINE GRAPHS USING GPLOT
18.2 CREATING BAR CHARTS AND PIE CHARTS
18.3 DEFINING GRAPH PATTERNS
18.4 CREATING STACKED BAR CHARTS
18.5 CREATING MEAN BARS USING GCHART
18.6 CREATING BOXPLOTS
18.7 GOING DEEPER: CREATING AN INTERACTIVE BAR USING ODS
18.8 GOING DEEPER: SGPLOTS
18.9 OTHER WAYS TO CUSTOMIZE PLOTS
19: CREATING CUSTOM REPORTS
19.1 USING PROC TABULATE
19.2 USING PROC REPORT
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