Fundamental statistics for the behavioral sciences

Machine generated contents note: 1.1. Changing Field --
1.2. Importance of Context --
1.3. Basic Terminology --
1.4. Selection among Statistical Procedures --
1.5. Using Computers --
1.6. Summary --
1.7. Quick Review --
1.8. Exercises --
2.1. Scales of Measurement --
2.2. Variables --
2.3. Random Sampling --
2.4. Notation --
2.5. Summary --
2.6. Quick Review --
2.7. Exercises --
3.1. Plotting Data --
3.2. Stem-and-Leaf Displays --
3.3. Reading Graphs --
3.4. Alternative Methods of Plotting Data --
3.5. Describing Distributions --
3.6. Using SPSS to Display Data --
3.7. Summary --
3.8. Quick Review --
3.9. Exercises --
4.1. Mode --
4.2. Median --
4.3. Mean --
4.4. Relative Advantages and Disadvantages of the Mode, the Median, and the Mean --
4.5. Obtaining Measures of Central Tendency Using SPSS and R --
4.6. Simple Demonstration-Seeing Statistics --
4.7. Summary --
4.8. Quick Review --
4.9. Exercises --
5.1. Range --
5.2. Interquartile Range and Other Range Statistics --
5.3. Average Deviation --
5.4. Variance --
5.5. Standard Deviation --
5.6. Computational Formulae for the Variance and the Standard Deviation --
5.7. Mean and the Variance as Estimators --
5.8. Boxplots: Graphical Representations of Dispersion and Extreme Scores --
5.9. Return to Trimming --
5.10. Obtaining Measures of Dispersion Using SPSS & R --
5.11. Moon Illusion --
5.12. Seeing Statistics --
5.13. Summary --
5.14. Quick Review --
5.15. Exercises --
6.1. Normal Distribution --
6.2. Standard Normal Distribution --
6.3. Setting Probable Limits on an Observation --
6.4. Measures Related to z --
6.5. Seeing Statistics --
6.6. Summary --
6.7. Quick Review --
6.8. Exercises --
7.1. Probability --
7.2. Basic Terminology and Rules --
7.3. Application of Probability to Controversial Issues --
7.4. Writing Up the Results --
7.5. Discrete Versus Continuous Variables --
7.6. Probability Distributions for Discrete Variables --
7.7. Probability Distributions for Continuous Variables --
7.8. Summary --
7.9. Quick Review --
7.10. Exercises --
8.1. Sampling Distributions and the Standard Error --
8.2. Two More Examples Involving Course Evaluations and Human Decision Making --
8.3. Hypothesis Testing --
8.4. Null Hypothesis --
8.5. Test Statistics and Their Sampling Distributions --
8.6. Using the Normal Distribution to Test Hypotheses --
8.7. Type I and Type II Errors --
8.8. One- and Two-Tailed Tests --
8.9. Seeing Statistics --
8.10. Final Example --
8.11. Back to Course Evaluations and Sunk Costs --
8.12. Summary --
8.13. Quick Review --
8.14. Exercises --
9.1. Scatter Diagrams --
9.2. Example: The Relationship Between the Pace of Life and Heart Disease --
9.3. Covariance --
9.4. Pearson Product-Moment Correlation Coefficient (r) --
9.5. Correlations with Ranked Data --
9.6. Factors That Affect the Correlation --
9.7. Beware Extreme Observations --
9.8. Correlation and Causation --
9.9. If Something Looks Too Good to Be True, Perhaps It Is --
9.10. Testing the Significance of a Correlation Coefficient --
9.11. Confidence Intervals on Correlation Coefficients --
9.12. Intercorrelation Matrices --
9.13. Other Correlation Coefficients --
9.14. Using SPSS to Obtain Correlation Coefficients --
9.15. r2 and the Magnitude of an Effect --
9.16. Seeing Statistics --
9.17. Review: Does Rated Course Quality Relate to Expected Grade? --
9.18. Summary --
9.19. Quick Review --
9.20. Exercises --
10.1. Relationship Between Stress and Health --
10.2. Basic Data --
10.3. Regression Line --
10.4. Accuracy of Prediction --
10.5. Influence of Extreme Values --
10.6. Hypothesis Testing in Regression --
10.7. Computer Solution Using SPSS --
10.8. Seeing Statistics --
10.9. Final Example for Review --
10.10. Regression Versus Correlation --
10.11. Summary --
10.12. Quick Review --
10.13. Exercises --
11.1. Overview --
11.2. Funding Our Schools --
11.3. Multiple Regression Equation --
11.4. Residuals --
11.5. Hypothesis Testing --
11.6. Refining the Regression Equation --
11.7. Special Section: Using R to Solve a Multiple Regression Problem --
11.8. Second Example: What Makes a Confident Mother? --
11.9. Third Example: Psychological Symptoms in Cancer Patients --
11.10. Summary --
11.11. Quick Review --
11.12. Exercises --
12.1. Sampling Distribution of the Mean --
12.2. Testing Hypotheses about Means when (Sv (B Is Known --
12.3. Testing a Sample Mean When (Sv (B Is Unknown (The One-Sample t Test) --
12.4. Factors That Affect the Magnitude of t and the Decision about H0 --
12.5. Second Example: The Moon Illusion --
12.6. How Large Is Our Effect? --
12.7. Confidence Limits on the Mean --
12.8. Using SPSS and R to Run One-Sample t Tests --
12.9. Good Guess Is Better than Leaving It Blank --
12.10. Seeing Statistics --
12.11. Confidence Intervals Can Be Far More Important than a Null Hypothesis Test --
12.12. Summary --
12.13. Quick Review --
12.14. Exercises --
13.1. Related Samples --
13.2. Student's t Applied to Difference Scores --
13.3. Crowd Within Is Like the Crowd Without --
13.4. Advantages and Disadvantages of Using Related Samples --
13.5. How Large an Effect Have We Found?-Effect Size --
13.6. Confidence Limits on Change --
13.7. Using SPSS and R for t Tests on Related Samples --
13.8. Writing Up the Results --
13.9. Summary --
13.10. Quick Review --
13.11. Exercises --
14.1. Distribution of Differences Between Means --
14.2. Heterogeneity of Variance --
14.3. Nonnormality of Distributions --
14.4. Second Example with Two Independent Samples --
14.5. Effect Size Again --
14.6. Confidence Limits on P1 --
P2 --
14.7. Confidence Limits on Effect Size --
14.8. Plotting the Results --
14.9. Writing Up the Results --
14.10. Do Lucky Charms Work? --
14.11. Seeing Statistics --
14.12. Summary --
14.13. Quick Review --
14.14. Exercises --
15.1. Basic Concept of Power --
15.2. Factors Affecting the Power of a Test --
15.3. Calculating Power the Traditional Way --
15.4. Power Calculations for the One-Sample t Test --
15.5. Power Calculations for Differences Between Two Independent Means --
15.6. Power Calculations for the t Test for Related Samples --
15.7. Power Considerations in Terms of Sample Size --
15.8. You Don't Have to Do It by Hand --
15.9. Post-hoc (Retrospective) Power --
15.10. Summary --
15.11. Quick Review --
15.12. Exercises --
16.1. General Approach --
16.2. Logic of the Analysis of Variance --
16.3. Calculations for the Analysis of Variance --
16.4. Unequal Sample Sizes --
16.5. Multiple Comparison Procedures --
16.6. Violations of Assumptions --
16.7. Size of the Effects --
16.8. Writing Up the Results --
16.9. Final Worked Example --
16.10. Seeing Statistics --
16.11. Summary --
16.12. Quick Review --
16.13. Exercises --
17.1. Factorial Designs --
17.2. Eysenck Study --
17.3. Interactions --
17.4. Simple Effects --
17.5. Measures of Association and Effect Size --
17.6. Reporting the Results --
17.7. Unequal Sample Sizes --
17.8. Masculine Overcompensation Thesis: It's a Male Thing --
17.9. Using SPSS for Factorial Analysis of Variance --
17.10. Seeing Statistics --
17.11. Summary --
17.12. Quick Review --
17.13. Exercises --
18.1. Example: Depression as a Response to an Earthquake --
18.2. Multiple Comparisons --
18.3. Effect Size --
18.4. Assumptions Involved in Repeated-Measures Designs --
18.5. Advantages and Disadvantages of Repeated-Measures Designs --
18.6. Writing Up The Results --
18.7. Final Worked Example --
18.8. Summary --
18.9. Quick Review --
18.10. Exercises --
19.1. One Classification Variable: The Chi-Square Goodness-of-Fit Test --
19.2. Two Classification Variables: Analysis of Contingency Tables --
19.3. Possible Improvements on Standard Chi-Square --
19.4. Chi-Square for Larger Contingency Tables --
19.5. Problem of Small Expected Frequencies --
19.6. Use of Chi-Square as a Test on Proportions --
19.7. Measures of Effect Size --
19.8. Final Worked Example --
19.9. Second Example of Writing up Results --
19.10. Seeing Statistics --
19.11. Summary --
19.12. Quick Review --
19.13. Exercises --
20.1. Traditional Nonparametric Tests --
20.2. Randomization Tests --
20.3. Measures of Effect Size --
20.4. Bootstrapping --
20.5. Writing up the Results of the Study of Maternal Adaptation --
20.6. Summary --
20.7. Quick Review --
20.8. Exercises --
21.1. Meta-Analysis --
21.2. Brief Review of Effect Size Measures --
21.3. Example[—]Child and Adolescent Depression --
21.4. Second Example[—]Nicotine Gum and Smoking Cessation --
21.5. Quick Review --
21.6. Exercises.