Advanced and Multivariate Statistical Methods
Description
* Stresses the conceptual and practical aspects for students who do not need emphasis on the underlying mathematical theory.
* Students learn not only the purpose of and how to compute the statistics using SPSS, they also learn the logic behind the techniques and how to test the underlying assumptions.
* Students are shown how to interpret, present, and write up the results for each technique.
* Exercises allow students to practice their newly acquired skills. The answer key will be provided with professors' copies.
* If your students are overwhelmed by advanced statistics texts that are too technical and mathematical, you should examine this highly applied approach to multivariate statistics. Covers why, what, when and how. Ideal for nonmath majors.
* The numerous screenshots and examples of output make it easy for students to follow the text.
* Each statistical method is followed by an explanation of why a student might use that method, including a discussion of its purpose and sample research questions it can address.
* The authors also show a sample study with an example of how to write up the results. Students see firsthand how to present their statistical findings.
* Although SPSS is the program that is illustrated, students using any program will benefit greatly from the conceptual material.
* All the statistics traditionally covered in a second-level course are included.
* Stresses the conceptual and practical aspects for students who do not need emphasis on the underlying mathematical theory.
* Students learn not only the purpose of and how to compute the statistics using SPSS, they also learn the logic behind the techniques and how to test the underlying assumptions.
* Students are shown how to interpret, present, and write up the results for each technique.
* Exercises allow students to practice their newly acquired skills. The answer key will be provided with professors' copies.
* If your students are overwhelmed by advanced statistics texts that are too technical and mathematical, you should examine this highly applied approach to multivariate statistics. Covers why, what, when and how. Ideal for nonmath majors.
* The numerous screenshots and examples of output make it easy for students to follow the text.
* Each statistical method is followed by an explanation of why a student might use that method, including a discussion of its purpose and sample research questions it can address.
* The authors also show a sample study with an example of how to write up the results. Students see firsthand how to present their statistical findings.
* Although SPSS is the program that is illustrated, students using any program will benefit greatly from the conceptual material.
More details
Other editions
New editions
Person
Content
Chapter 1: Introduction to Multivariate Statistics
Chapter 2: A Guide to Multivariate Techniques
Chapter 3: Pre-Analysis Data Screening
Chapter 4: Factorial Analysis of Variance
Chapter 5: Analysis of Covariance
Chapter 6: Multivariate Analysis of Variance and Covariance
Chapter 7: Multiple Regression
Chapter 8: Path Analysis
Chapter 9: Factor Analysis
Chapter 10: Discriminant Analysis
Chapter 11: Logistic Regression
Appendix A: SPSS Data Sets
Appendix B: The Chi-Square Distribution
Glossary
References
Subject Index