Skip to content

SPSS 16. 0 Guide to Data Analysis

Best in textbook rentals since 2012!

ISBN-10: 0136061362

ISBN-13: 9780136061366

Edition: 2nd 2009

Authors: Marija J. Norusis

List price: $88.00
Blue ribbon 30 day, 100% satisfaction guarantee!
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!

Description:

TheSPSS 16.0 Guide to Data Analysisis a friendly introduction to both data analysis and SPSS, the worldrsquo;s leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With theSPSS 16.0 Guide to Data Analysis, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS. nbsp; Author Marija Noruscaron;is incorporates a wealth of data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library…    
Customers also bought

Book details

List price: $88.00
Edition: 2nd
Copyright year: 2009
Publisher: Prentice Hall Higher Education
Publication date: 1/1/2008
Binding: Mixed Media
Pages: 672
Size: 7.25" wide x 9.25" long x 1.00" tall
Weight: 2.134
Language: English

Contents at a glance
Getting started with SPSS
Setting up a data file
using the online tutorial and Help system
evaluating strategies for acquiring data
Describing Data:Histograms, bar charts, stem and leaf plots, boxplots
scatterplots
tables and summary statistics
Testing Hypotheses:One sample t-test
paired and two sample t-tests
oneway and twoway analysis of variance
chi-square tests
nonparametric tests
Examining Relationships:Measures of association
linear regression and correlation
multiple regression
examining residuals and other diagnostics
Appendices Include detailed instructions for producing charts with SPSS, and a thorough overview of the facilities for transforming and selecting data prior to analysis