SAS Statistics by Example
SAS Institute, 22 de ago de 2011 - 274 páginas
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.
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Chapter 2 Descriptive Statistics Continuous Variables
Chapter 3 Descriptive Statistics Categorical Variables
Chapter 4 Descriptive Statistics Bivariate Associations
Chapter 5 Inferential Statistics OneSample Tests
Chapter 6 Inferential Statistics TwoSample Tests
Chapter 7 Inferential Statistics Comparing More than Two Means
Chapter 8 Correlation and Regression
Chapter 9 Multiple Regression
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ANOVA Book_Sales box plot Cary categorical variables chapter cholesterol Cody columns Conducting a One-Sample continuous variables Copyright correlations create data points DATA step data values data=example.Blood_Pressure data=store default Demonstrating dependent variable Descriptive Statistics display dummy variables Electronics_Sales heart attack histogram influential observations INPUT statement interaction keyword labeled Logistic Regression LSMEANS missing values model Pushups MODEL statement Music_Sales nonparametric normal distribution North Carolina null hypothesis odds ratio ODS Graphics ODS Statistical Graphics One-Sample t-test one-way option outcome output shows p-value paired Power and Sample predictor variables PROC CORR PROC FREQ PROC GLM PROC MEANS proc print PROC RANK PROC SGPLOT PROC SGSCATTER PROC TTEST PROC UNIVARIATE produce Q-Q plot R-square Random Sample request residuals SAS data set SAS Institute Inc SAS programs selection method specify standard deviation Statistics by Example Stepwise Studentized residuals Subj variable names variance Wilcoxon Wilcoxon signed-rank test