Home
»
Using R With Multivariate Statistics
Using R With Multivariate Statistics
★★★★★
★★★★★
Regular price
€79.99
Regular price
€80.99
Sale
Sale price
€79.99
A01=Randall E. Schumacker
Age Group_Uncategorized
Age Group_Uncategorized
Author_Randall E. Schumacker
automatic-update
Category1=Non-Fiction
Category=GPS
Category=UFM
COP=United States
Data analysis
Delivery_Delivery within 10-20 working days
eq_computing
eq_isMigrated=2
eq_non-fiction
Language_English
Multivariate
PA=To order
Price_€50 to €100
PS=Active
Quantitative Analysis
R
softlaunch
Statistical analysis
Statistical research
Statistical Software
Statistics
Product details
- ISBN 9781483377964
- Weight: 710g
- Dimensions: 187 x 231mm
- Publication Date: 08 Sep 2015
- Publisher: SAGE Publications Inc
- Publication City/Country: US
- Product Form: Paperback
- Language: English
Delivery/Collection within 10-20 working days
Our Delivery Time Frames Explained
2-4 Working Days: Available in-stock
10-20 Working Days: On Backorder
Will Deliver When Available: On Pre-Order or Reprinting
We ship your order once all items have arrived at our warehouse and are processed. Need those 2-4 day shipping items sooner? Just place a separate order for them!
Using R with Multivariate Statistics is a quick guide to using R, free-access software available for Windows and Mac operating systems that allows users to customize statistical analysis. Designed to serve as a companion to a more comprehensive text on multivariate statistics, this book helps students and researchers in the social and behavioral sciences get up to speed with using R. It provides data analysis examples, R code, computer output, and explanation of results for every multivariate statistical application included. In addition, R code for some of the data set examples used in more comprehensive texts is included, so students can run examples in R and compare results to those obtained using SAS, SPSS, or STATA. A unique feature of the book is the photographs and biographies of famous persons in the field of multivariate statistics.
Dr. Randall E. Schumacker is professor of educational research at the University of Alabama. He has written and co-edited several books, including A Beginner’s Guide to Structural Equation Modeling, Third Edition, Advanced Structural Equation Modeling: Issues and Techniques, Interaction and Non-Linear Effects in Structural Equation Modeling, New Developments and Techniques in Structural Equation Modeling, Understanding Statistical Concepts Using S-PLUS, Understanding Statistics Using R, and Learning Statistics Using R. Dr. Schumacker was the founder and is now emeritus editor of Structural Equation Modeling: A Multidisciplinary Journal, and has established the Structural Equation Modeling Special Interest Group within the American Educational Research Association (AERA). He is also the emeritus editor of Multiple Linear Regression Viewpoints, the oldest journal sponsored by AERA (Multiple Linear Regression: General Linear Model Special Interest Group). Dr. Schumacker has conducted international and national workshops, has served on the editorial board of several journals, and currently pursues his research interests in statistics and structural equation modeling. He was the 1996 recipient of the Outstanding Scholar Award and the 1998 recipient of the Charn Oswachoke International Award. In 2010, he launched the DecisionKit App for the iPhone, iPad, and iTouch, which can assist researchers in making decisions about which measurement, research design, or statistic to use in their research projects. In 2011, he received the Apple iPad Award. In, 2012, he received the CIT Faculty Technology Award. In 2013, he received the McCrory Faculty Excellence in Research Award from the College of Education at the University of Alabama. In 2014, Dr. Schumacker was the recipient of the Structural Equation Modeling Service Award at AERA.
Qty: