The SPSS 16.0 Guide to Data Analysis is a friendly introduction to both data analysis and SPSS, the world’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 the SPSS 16.0 Guide to Data Analysis, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS.

Author Marija Norušis 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 patronage, and the importance of manners. These data files are supplied with the book and are used throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun!

Data CD-ROM included.

Marija Norušis earned a Ph.D. in biostatistics from the University of Michigan. She was SPSS's first professional statistician. McGraw-Hill published her first book, The SPSS Introductory Guide. Since then she has written numerous volumes of highly acclaimed SPSS documentation, and textbooks that demystify statistics and SPSS. Dr. Norušis has been on the faculties of the University of Chicago and Rush Medical College, teaching statistics to diverse audiences. When not working on SPSS guides, Marija analyzes real data as a statistical consultant.

For those whose Lithuanian is rusty:

"Marija" is pronounced "Maria," not "Mar-eye-ja."

"Norušis" is pronounced "Norooshis," not "Neurosis."

Part 1   Getting started with SPSS:

Setting up a data file; using the online tutorial and Help system; evaluating strategies for acquiring data

Part 2   Describing Data:

Histograms, bar charts, stem and leaf plots, boxplots; scatterplots; tables and summary statistics

Part 3   Testing Hypotheses:

One sample t-test; paired and two sample t-tests; oneway and twoway analysis of variance; chi-square tests; nonparametric tests

Part 4   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.