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A Handbook of Statistical Analyses Using SAS by Geoff Der and Brian S. Everitt (
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關於物品
物品細節
- 物品狀況
- 很新
- 賣家備註
- “No use, no details for consideration from storage”
- Country of Origin
- United States
- Series
- No
- Custom Bundle
- No
- Educational Level
- Pro
- Personalized
- No
- Features
- Trade Paperback
- MPN
- No
- Level
- Pro
- ISBN
- 9781584887843
關於產品
Product Identifiers
Publisher
CRC Press LLC
ISBN-10
1584887842
ISBN-13
9781584887843
eBay Product ID (ePID)
58237589
Product Key Features
Number of Pages
416 Pages
Language
English
Publication Name
Handbook of Statistical Analyses Using Sas
Subject
Mathematical & Statistical Software, Probability & Statistics / General
Publication Year
2008
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
3.4 in
Item Weight
26.6 Oz
Item Length
9.3 in
Item Width
6 in
Additional Product Features
Edition Number
3
Intended Audience
College Audience
LCCN
2008-021184
Dewey Edition
22
TitleLeading
A
Illustrated
Yes
Dewey Decimal
519.5
Table Of Content
Introduction to SAS. Data Description and Simple Inference: Mortality and Water Hardness in the United Kingdom. Simple Inference for Categorical Data: From Sandflies to Organic Particulates in the Air. Analysis of Variance I: Treating Hypertension. Analysis of Variance II: School Attendance among Australian Children. Simple Linear Regression: Alcohol Consumption and Cirrhosis Deaths and How Old Is the Universe? Multiple Regression: Determinants of the Crime Rate in States of the United States. Logistic Regression: Psychiatry Screening, Plasma Proteins, Danish Do-It-Yourself, and Lower Back Pain. Generalized Linear Models: Polyposis and School Attendance among Australian School Children. Generalized Additive Models: Burning Rubber and Air Pollution in the United States. Analysis of Variance of Repeated Measures Visual Acuity. Longitudinal Data I: Treatment of Postnatal Depression. Longitudinal Data II: Linear Mixed Models. Longitudinal Data III: Generalized Estimating Equations and Generalized Mixed Models. Survival Analysis: Gastric Cancer, the Treatment of Heroin Addicts, and Heart Transplants. Principal Components Analysis and Factor Analysis: Olympic Decathlon and Statements about Pain. Cluster Analysis: Air Pollution in the United States. Discriminant Function Analysis: Classifying Tibetan Skulls. Correspondence Analysis: Smoking and Motherhood, Sex and the Single Girl, and European Stereotypes. Appendix. References. Index.
Edition Description
Revised edition,Handbook (Instructor's),New Edition
Synopsis
Remaining the go-to resource for learning how to use SAS for many kinds of statistical analysis, this third edition of a bestseller explains how to conduct a range of statistical analyses using the latest version of SAS. It illustrates each type of analysis with numerous real-world data examples, such as environmental causes of diseases, hypertension treatment, and gastric cancer treatment. This edition presents the new graphics procedures of SAS 9.2. It also includes more end-of-chapter exercises and selected answers in the appendix, along with a solutions manual that provides SAS code, output, and comments. The SAS programs and data sets used in the book are available online., Updated to reflect SAS 9.2, A Handbook of Statistical Analyses using SAS, Third Edition continues to provide a straightforward description of how to conduct various statistical analyses using SAS. Each chapter shows how to use SAS for a particular type of analysis. The authors cover inference, analysis of variance, regression, generalized linear models, longitudinal data, survival analysis, principal components analysis, factor analysis, cluster analysis, discriminant function analysis, and correspondence analysis. They demonstrate the analyses through real-world examples, including methadone maintenance treatment, the relation of cirrhosis deaths to alcohol consumption, a sociological study of children, heart transplant treatment, and crime rate determinants. With the data sets and SAS code available online, this book remains the go-to resource for learning how to use SAS for many kinds of statistical analysis. It serves as a stepping stone to the wider resources available to SAS users.
LC Classification Number
QA276.4.E88 2008
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