Pdq Statistics

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Book Description
Practical handbook on understanding statistics for anyone that must occasionally interpret the results section of a research article in scientific journals.
PDQ Statistics offers an expert overview of all major statistical methods, giving the reader a thorough understanding of statistics and how they are used in research articles. The book covers the major categories variable and descriptive statistics, parametric statistics, non-parametric statistics, and multivariate statistics. The explanations are clear, succinct, and loaded with practical examples. This third edition includes new chapters on hierarchical and logistic regression, path analysis, and structural equation modeling. PDQ Statistics, Third Edition also helps the reader identify those statistical analyses with basic flaws in design or research. The books attractive design and humorous writing style make the subject matter accessible and engaging.

Book Info
McMaster Univ., Hamilton, Canada. Pocket guide on understanding statistics, for anyone who must occasionally interpret the results section of a research article in scientific journals. Not intended as a textbook; light, often humorous writing style.

Part One Variables and Descriptive Statistics
1. Names and Numbers: Types of Variables
2. Describing Data
Part Two Parametric Statistics
3. Statistical Inference
4. Comparison of Means of Two Samples: The t Test
5. Comparison Among Many Means: Analysis of Variance
6. Relationship Between Interval and Ratio Variables: Linear and Multiple Regression
7. Analysis of Covariance
8. Variations on Linear Regression: Logistic Regression, General Linear Model, and Hierarchical Linear Models
9. Time Series Analysis
Part Three NonParametric Statistics
10. Nonparametric Tests of Significance
11. Nonparametric Measures of Association
12. Advanced Nonparametric Methods
Part Four Multivariate Statistics
13. Introduction to Multivariate Statistics
14. Multivariate Analysis of Variance
15. Discriminant Function Analysis
16. Exploratory Factor Analysis
17. Path Analysis and Structural Equation Modeling
18. Cluster Analysis
19. Canonical Correlation
20. Reprise
21. Research Designs