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SPSS 16.0 Guide to Data Analysis (2nd Edition), by Marija Norusis
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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.
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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!
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Data CD-ROM included.
- Sales Rank: #1520630 in Books
- Published on: 2008-01-28
- Original language: English
- Number of items: 1
- Dimensions: 8.98" h x 1.02" w x 7.40" l,
- Binding: Paperback
- 672 pages
About the Author
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."
Most helpful customer reviews
21 of 22 people found the following review helpful.
Excellent Introduction to Statistical Analysis Using SPSS
By Edward Torpy
Marija Norusis is a great writer who can clearly articulate complex statistical concepts that the average person can understand. Her writing style is very conversational without sacrificing technical accuracy. Although this book is designed to be used as an introductory statistics book in a college course, it also serves as an excellent SPSS user's guide. The author describes the logic of hypothesis testing, the concept of "statistical significance", and the general concepts behind data analysis that the new data analyst can easily understand.
Part I. Getting Started with SPSS
1. Introduction
2. An Introductory Tour of SPSS
3. Sources of Data
Part II. Describing Data
4. Counting Responses
5. Computing Descriptive Statistics
6. Comparing Groups
7. Looking at Distributions
8. Counting Responses for Combinations of Variables
9. Plotting Data
Part III. Testing Hypotheses
10. Evaluating Results from Samples
11. The Normal Distribution
12. Testing a Hypothesis about a Single Mean
13. Testing a Hypothesis about Two Related Means
14. Testing a Hypothesis about Two Independent Means
15. One-Way Analysis of Variance
16. Two-Way Analysis of Variance
17. Comparing Observed and Expected Counts
18. Nonparametric Tests
Part IV. Examining Relationships
19. Measuring Association
20. Linear Regression and Correlation
21. Testing Regression Hypotheses
22. Analyzing Residuals
23. Building Multiple Regression Models
24. Multiple Regression Diagnostics
2 of 3 people found the following review helpful.
Impressed
By Alicia Jones
I am highly impressed with the book I bought from Amazon. I was pleasantly surprised to see the good shape the textbook which wasn't new was in.It looked like new.
2 of 3 people found the following review helpful.
superb
By Christopher Koch
This is EXACTLY what I needed. I spent the summer (09) going through it as a workbook. I appreciate the design, the material, the practice data. Money well spent.
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