Applied Statistics and the SAS Programming Language

ISBN-10: 0137436424
ISBN-13: 9780137436422
Edition: 4th 1997
List price: $62.00
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Description: Suitable for use by departments ranging from statistics and Engineering to Psychology and Education when the objective of the course is to learn to use the SAS programming language to perform statistical analysis. Applied Statistics and the SAS  More...

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Book details

List price: $62.00
Edition: 4th
Copyright year: 1997
Publisher: Prentice Hall PTR
Publication date: 4/21/1997
Binding: Paperback
Pages: 445
Size: 7.25" wide x 9.50" long x 0.75" tall
Weight: 1.430
Language: English

Suitable for use by departments ranging from statistics and Engineering to Psychology and Education when the objective of the course is to learn to use the SAS programming language to perform statistical analysis. Applied Statistics and the SAS Programming Language is intended to provide the applied researcher with the capacity to perform statistical analyses with SAS software without wading through pages of technical documentation.

Applied Statistics and Sas Software
A SAS Tutorial
Introduction
Computing with SAS Software: An Illustrative Example
Enhancing the Program
SAS Procedures
Overview of the SAS Data Step
Syntax of SAS Procedures
Comment Statements
References
Describing Data
Introduction
Describing Data
More Descriptive Statistics
Descriptive Statistics Broken Down by Subgroups
Frequency Distributions
Bar Graphs
Plotting Data
Creating Summary Data Sets with PROC MEANS an PROC UNIVARIATE
Outputting Statistics Other than Means
Creating a Summary Data Set to Contain a Median
Analyzing Categorical Data
Introduction
Questionnaire Design and Analysis
Adding Variable Labels
Adding Value Labels (Formats)
Recoding Data
Using a Format to Recode a Variable
Two-way Frequency Tables
A Shortcut Way of Requesting Multiple Tables
Computing Chi-square From Frequency Counts
A Useful Program for Multiple Chi-square Tables
McNemar's Test for Paired Data
Odds Ratios
Relative Risk
Chi-square Test for Trend
Mantel-Haenszel Chi-square for Stratified Tables and Meta Analysis
Check all that Apply Questions
Working with Date and Longitudinal Data
Introduction Processing Date Variables
Longitudinal Data
Most Recent (or Last) Visit per Patient
Computing Frequencies on Longitudinal Data Sets
Correlation and Regression
Introduction
Correlation
Significance of a Correlation Coefficient
How to Interpret a Correlation Coefficient
Partial Correlations
Linear Regression
Partitioning the Total Sum of Squares
Plotting the Points on the Regression Line
Plotting Residuals and Confidence Limits
Adding a Quadratic Term to the Regression Equation
Transforming Data
Computing Within-subject Slopes
T-Tests and Nonparametric Comparisons
Introduction
T-Test: Testing Differences Between Two Means
Random Assignment of Subjects
Two Independent Samples: Distribution Free Tests
One-Tailed versus Two-Tailed Tests
Paired T-Tests (Related Samples)
Analysis of Variance
Introduction
One-Way Analysis of Variance
Computing Contrasts
Analysis of Variance: Two Independent Variables
Interpreting Significant Interactions
N-Way Factorial Designs
Unbalanced Designs: PROC GLM. Analysis of Covariance
Repeated Measures Designs
Introduction
One-Factor Experiments
Using the REPEATED Statement of PROC ANOVA
Two-Factor Experiments with a Repeated Measure on One Factor
Two-Factor Experiments with Repeated Measures on Both Factors
Three-Factor Experiments with a Repeated Measure on the Last Factor
Three-Factor Experiments with Repeated Measures on Two Factors
Multiple Regression Analysis
Introduction
Designed Regression
Nonexperimental Regression
Stepwise Regressions
Creating and Using Dummy Variables
Logistic Regression
Factor Analysis
Introduction
Types of Factor Analysis
Principle Components Analysis
Oblique Rotations
Using Communalities Other than One
How to Reverse Item Scores
Psychometrics
Introduction
Using SAS Software to Score a Test
Generalizing the Program for a Variable Number of Questions
Creating a Better Looking Table Using PROC TABULATE
A Complete Test Scoring and Item Analysis Program
Test Reliability
Interrater Reliability
SAS Programming
The SAS INPUT Statement
Introduction
List Directed Input: Data Values Separated By Spaces
Reading Comma Delimited Data
Using INFORMATS with List Directed Data
Column Input
Pointers and Informats
Reading More than One Line per Subject
Changing the Order and Reading a Column More Than Once
Informat Lists
Holding the Line - Single and Double Trailing @'s
Suppressing the Error Messages for Invalid Data
Reading U

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