SAS statistics by example / Ron Cody.

Format:

Book

Author/Creator:

Cody, Ronald P., author.

Contributor:

SAS Institute.

Language:

English

Subjects (All):

SAS (Computer file).

Database management.

Mathematical statistics--Data processing.

Mathematical statistics.

SAS (Computer program language).

Physical Description:

1 online resource (1 v.) : ill.

Edition:

First edition.

Place of Publication:

Cary, North Carolina : SAS Institute Inc., [2011]

Language Note:

English

System Details:

text file

Summary:

In SAS Statistics by Example, Ron Cody offers up a cookbook approach for doing statistics with SAS. Structured specifically around the most commonly used statistical tasks or techniques--for example, comparing two means, ANOVA, and regression--this book provides an easy-to-follow, how-to approach to statistical analysis not found in other books. For each statistical task, Cody includes heavily annotated examples using ODS Statistical Graphics procedures such as SGPLOT, SGSCATTER, and SGPANEL that show how SAS can produce the required statistics. Also, you will learn how to test the assumptions for all relevant statistical tests. Major topics featured include descriptive statistics, one- and two-sample tests, ANOVA, correlation, linear and multiple regression, analysis of categorical data, logistic regression, nonparametric techniques, and power and sample size. This is not a book that teaches statistics. Rather, SAS Statistics by Example is perfect for intermediate to advanced statistical programmers who know their statistics and want to use SAS to do their analyses. This book is part of the SAS Press program.

Contents:

Intro

Contents

acknow

Chapter 1

Introduction

What is SAS

Statistical Tasks Performed by SAS

The Structure of SAS Programs

SAS Data Sets

SAS Display Manager

Excel Workbooks

Variable Types in SAS Data Sets

Temporary versus Permanent SAS Data Sets

Creating a SAS Data Set from Raw Data

Data Values Separated by Delimiters

Reading CSV Files

Data Values in Fixed Columns

Excel Files with Invalid SAS Variable Names

Other Sources of Data

Conclusions

Chapter 2

Computing Descriptive Statistics Using PROC MEANS

Descriptive Statistics Broken Down by a Classification Variable

Computing a 95% Confidence Interval and the Standard Error

Producing Descriptive Statistics, Histograms, and Probability Plots

Changing the Midpoint Values on the Histogram

Generating a Variety of Graphical Displays of Your Data

Displaying Multiple Box Plots for Each Value of a Categorical Variable

Chapter 3

Computing Frequency Counts and Percentages

Computing Frequencies on a Continuous Variable

Using Formats to Group Observations

Creating a Bar Chart Using PROC SGPLOT

Using ODS to Send Output to Alternate Destinations

Creating a Cross-Tabulation Table

Changing the Order of Values in a Frequency Table

Chapter 4

Producing a Simple Scatter Plot Using PROG GPLOT

Producing a Scatter Plot Using PROC SGPLOT

Creating Multiple Scatter Plots on a Single Page Using PROC SGSCATTER

Chapter 5

Conducting a One-Sample t-test Using PROC TTEST

Running PROC TTEST with ODS Graphics Turned On

Conducting a One-Sample t-test Using PROC UNIVARIATE

Testing Whether a Distribution is Normally Distributed

Tests for Other Distributions

Chapter 6.

Introduction

Conducting a Two-Sample t-test

Testing the Assumptions for a t-test

Customizing the Output from ODS Statistical Graphics

Conducting a Paired t-test

Assumption Violations

Chapter 7

A Simple One-way Design

Conducting Multiple Comparison Tests

Using ODS Graphics to Produce a Diffogram

Two-way Factorial Designs

Analyzing Factorial Models with Significant Interactions

Analyzing a Randomized Block Design

Chapter 8

Producing Pearson Correlations

Generating a Correlation Matrix

Creating HTML Output with Data Tips

Generating Spearman Nonparametric Correlations

Running a Simple Linear Regression Model

Using ODS Statistical Graphics to Investigate Influential Observations

Using the Regression Equation to Do Prediction

A More Efficient Way to Compute Predicted Values

Chapter 9

Fitting Multiple Regression Models

Producing Separate Plots Instead of a Panel

Choosing the Best Model (Cp and Hocking's Criteria)

Forward, Backward, and Stepwise Selection Methods

Forcing Selected Variables into a Model

Creating Dummy (Design) Variables for Regression

Detecting Collinearity

Influential Observations in Multiple Regression Models

Chapter 10

Rearranging Rows and Columns in a Table

Tables with Expected Values Less Than 5 (Fisher's Exact Test)

Computing Chi-Square from Frequency Data

Using a Chi-Square Macro

A Short-Cut Method for Requesting Multiple Tables

Computing Coefficient Kappa-A Test of Agreement

Computing Tests for Trends

Computing Chi-Square for One-Way Tables

Chapter 11

Running a Logistic Regression Model with One Categorical Predictor Variable.

Running a Logistic Regression Model with One Continuous Predictor Variable

Using a Format to Create a Categorical Variable from a Continuous Variable

Using a Combination of Categorical and Continuous Variables in a Logistic Regression Model

Running a Logistic Regression with Interactions

Chapter 12

Performing a Wilcoxon Rank-Sum Test

Performing a Wilcoxon Signed-Rank Test (for Paired Data)

Performing a Kruskal-Wallis One-Way ANOVA

Comparing Spread: The Ansari-Bradley Test

Converting Data Values into Ranks

Using PROC RANK to Group Your Data Values

Chapter 13

Computing the Sample Size for an Unpaired t-Test

Computing the Power of an Unpaired t-Test

Computing Sample Size for an ANOVA Design

Computing Sample Sizes (or Power) for a Difference in Two Proportions

Using the SAS Power and Sample Size Interactive Application

Chapter 14

Taking a Simple Random Sample

Taking a Random Sample with Replacement

Creating Replicate Samples using PROC SURVEYSELECT

References

Index.

Notes:

Bibliographic Level Mode of Issuance: Monograph

Includes bibliographical references and index.

Description based on print version record.

ISBN:

9781629590226

1629590223

9781612900124

1612900127

OCLC:

817691713