This text takes a traditional approach to teaching the basic statistical concepts and methods used in behavioral research. McCall emphasizes building an understanding of the logic of statistics rather than stressing the mechanics. Similarly, the data for computational problems has been kept simple, so students can focus on the rationale and outcome of techniques instead of the calculations themselves. Behavioral research issues are built into the problems and exercises.
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Part I: Descriptive Statistics. 1. The Study Of Statistics. Why Study Statistics? Descriptive and Inferential Statistics. Measurement. Summation sign. Summary. 2. Frequency Distributions And Graphing. Types of Frequency Distributions. Constructing Frequency Distributions with Class Intervals. Graphs of Frequency Distributions. How Distributions Differ. Summary. 3. Characteristics Of Distributions. Indicators of Central Tendency. Indicators of Variability. Populations and Samples. A Note on Calculators and Computers. Summary. 4. Elements Of Exploratory Data Analysis. Stem and Leaf Displays. Resistant Indicators. Summary. 5. Indicators Of Relative Standing. Percentiles. Changing the Properties of Scales. Standard Scores and the Normal Distribution. Summary. 6. Regression. Linear Relationships. Regression Constants and the Regression Line. Standard Error of Estimate. Summary. 7. Correlation. The Pearson Product-Moment Correlation Coefficient. Properties of the Correlation Coefficient. Sampling Factors that Change the Correlation Coefficient. Causality and Correlation. Summary. Part II: Inferential Statistics. 8. Sampling, Sampling Distributions, And Probability. Methods of Sampling. Sampling Distributions and Sampling Error. Probability and its Application to Hypothesis Testing. Estimation. Summary. 9. Introduction To Hypothesis Testing: Terminology And Theory. Statistical Terminology. Hypothesis Testing When Alpha X is Estimated by Sigma X. Summary. 10. Elementary Techniques Of Hypothesis Testing. Inferences About the Difference Between Means. Inferences About Correlation Coefficients. A Comparison of the Difference Between Means and Correlation. Statistics in the Journals. Summary. 11. Beyond Hypothesis Testing: Effect Size And Interval Estimation. Beyond Hypothesis Testing. Indices of Size. Interval Estimation. Summary. Part III: Special Topics. 12. Introduction To Research Design. Scientific Questions. Operationalizing. Data Collection and Data Analysis. Conclusions and Interpretations. The Research Report. Ethical Considerations. Summary. 13. Topics On Probability. Set Theory. Simple Classical Probability. Probability of Complex Events. Methods of Counting. Summary. 14. Simple Analysis Of Variance. Logic of the Analysis of Variance. Computational Procedures. Comparisons Between Specific Means. Size of Relationship. Summary. 15. Two-Factor Analysis Of Variance. Two-Factor Classification. Logic of Two-Factor Analysis of Variance. Computational Procedures. Summary. 16. Nonparametric Techniques. Parametric and Nonparametric Tests. Tests on Independent Samples. Tests on Correlated Samples. Rank-Order Correlation. Summary. Appendix 1: Math Review. Appendix 2: Tables. Appendix 3: Symbols. Appendix 4: Terms. Appendix 5: Answers. Index.
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