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Preface to the Instructor | p. xi |
Introduction to the Student | p. xvi |
Displaying the Order in a Group of Numbers Using Tables and Graphs | p. 1 |
The Two Branches of Statistical Methods | p. 2 |
Some Basic Concepts | p. 3 |
Important Trivia for Poetic Statistics Students | p. 6 |
Frequency Tables | p. 7 |
Histograms | p. 10 |
Math Anxiety, Statistics Anxiety, and You: A Message for Those of You Who Are Truly Worried About This Course | p. 12 |
Shapes of Frequency Distributions | p. 15 |
Controversy: Misleading Graphs | p. 19 |
Frequency Tables and Histograms in Research Articles | p. 21 |
Summary | p. 23 |
Key Terms | p. 24 |
Example Worked-Out Problems | p. 24 |
Practice Problems | p. 25 |
Using SPSS | p. 29 |
Chapter Note | p. 32 |
Central Tendency and Variability | p. 33 |
Central Tendency | p. 34 |
Variability | p. 43 |
The Sheer Joy (Yes, Joy) of Statistical Analysis | p. 51 |
Controversy: The Tyranny of the Mean | p. 52 |
Gender, Ethnicity, and Math Performance | p. 53 |
Central Tendency and Variability in Research Articles | p. 55 |
Summary | p. 57 |
Key Terms | p. 57 |
Example Worked-Out Problems | p. 57 |
Practice Problems | p. 59 |
Using SPSS | p. 62 |
Chapter Notes | p. 65 |
Some Key Ingredients for Inferential Statistics: Z Scores, the Normal Curve, Sample versus Population, and Probability | p. 67 |
Z Scores | p. 68 |
The Normal Curve | p. 73 |
de Moivre, the Eccentric Stranger Who Invented the Normal Curve | p. 74 |
Sample and Population | p. 83 |
Surveys, Polls, and 1948's Costly "Free Sample" | p. 86 |
Probability | p. 88 |
Pascal Begins Probability Theory at the Gambling Table, Then Learns to Bet on God | p. 89 |
Controversies: Is the Normal Curve Really So Normal? and Using Nonrandom Samples | p. 93 |
Z Scores, Normal Curves, Samples and Populations, and Probabilities in Research Articles | p. 95 |
Advanced Topics: Probability Rules and Conditional Probabilities | p. 96 |
Summary | p. 97 |
Key Terms | p. 98 |
Example Worked-Out Problems | p. 99 |
Practice Problems | p. 102 |
Using SPSS | p. 105 |
Chapter Notes | p. 106 |
Introduction to Hypothesis Testing | p. 107 |
A Hypothesis-Testing Example | p. 108 |
The Core Logic of Hypothesis Testing | p. 109 |
The Hypothesis-Testing Process | p. 110 |
One-Tailed and Two-Tailed Hypothesis Tests | p. 119 |
Controversy: Should Significance Tests Be Banned? | p. 124 |
Jacob Cohen, the Ultimate New Yorker: Funny, Pushy, Brilliant, and Kind | p. 126 |
Hypothesis Tests in Research Articles | p. 127 |
Summary | p. 128 |
Key Terms | p. 129 |
Example Worked-Out Problems | p. 129 |
Practice Problems | p. 131 |
Chapter Notes | p. 136 |
Hypothesis Tests with Means of Samples | p. 137 |
The Distribution of Means | p. 138 |
Hypothesis Testing with a Distribution of Means: The Z Test | p. 146 |
More About Polls: Sampling Errors and Errors in Thinking About Samples | p. 147 |
Controversy: Marginal Significance | p. 153 |
Hypothesis Tests About Means of Samples (Z Tests) and Standard Errors in Research Articles | p. 154 |
Advanced Topic: Estimation, Standard Errors, and Confidence Intervals | p. 156 |
Advanced Topic Controversy: Confidence Intervals versus Significance Tests | p. 162 |
Advanced Topic: Confidence Intervals in Research Articles | p. 163 |
Summary | p. 163 |
Key Terms | p. 164 |
Example Worked-Out Problems | p. 164 |
Practice Problems | p. 167 |
Chapter Notes | p. 173 |
Making Sense of Statistical Significance: Decision Errors, Effect Size, and Statistical Power | p. 175 |
Decision Errors | p. 175 |
Effect Size | p. 179 |
Effect Sizes for Relaxation and Meditation: A Restful Meta-Analysis | p. 184 |
Statistical Power | p. 187 |
What Determines the Power of a Study? | p. 191 |
The Power of Typical Psychology Experiments | p. 199 |
The Role of Power When Planning a Study | p. 203 |
The Role of Power When Interpreting the Results of a Study | p. 205 |
Controversy: Statistical Significance versus Effect Size | p. 208 |
Decision Errors, Effect Size, and Power in Research Articles | p. 210 |
Advanced Topic: Figuring Statistical Power | p. 212 |
Summary | p. 214 |
Key Terms | p. 215 |
Example Worked-Out Problems | p. 215 |
Practice Problems | p. 217 |
Chapter Note | p. 221 |
Introduction to t Tests: Single Sample and Dependent Means | p. 222 |
The t Test for a Single Sample | p. 223 |
William S. Gosset, Alias "Student": Not a Mathematician, But a Practical Man | p. 224 |
The t Test for Dependent Means | p. 236 |
Assumptions of the t Test for a Single Sample and the t Test for Dependent Means | p. 247 |
Effect Size and Power for the t Test for Dependent Means | p. 247 |
Controversy: Advantages and Disadvantages of Repeated-Measures Designs | p. 250 |
The Power of Studies Using Difference Scores: How the Lanarkshire Milk Experiment Could Have Been Milked for More | p. 251 |
Single Sample t Tests and Dependent Means t Tests in Research Articles | p. 252 |
Summary | p. 253 |
Key Terms | p. 254 |
Example Worked-Out Problems | p. 254 |
Practice Problems | p. 258 |
Using SPSS | p. 265 |
Chapter Notes | p. 268 |
The t Test for Independent Means | p. 270 |
The Distribution of Differences Between Means | p. 271 |
Hypothesis Testing with a t Test for Independent Means | p. 278 |
Assumptions of the t Test for Independent Means | p. 286 |
Monte Carlo Methods: When Mathematics Becomes Just an Experiment, and Statistics Depend on a Game of Chance | p. 286 |
Effect Size and Power for the t Test for Independent Means | p. 288 |
Review and Comparison of the Three Kinds of t Tests | p. 290 |
Controversy: The Problem of Too Many t Tests | p. 291 |
The t Test for Independent Means in Research Articles | p. 292 |
Advanced Topic: Power for the t Test for Independent Means When Sample Sizes Are Not Equal | p. 293 |
Summary | p. 294 |
Key Terms | p. 295 |
Example Worked-Out Problems | p. 295 |
Practice Problems | p. 298 |
Using SPSS | p. 305 |
Chapter Notes | p. 309 |
Introduction to the Analysis of Variance | p. 310 |
Basic Logic of the Analysis of Variance | p. 311 |
Sir Ronald Fisher, Caustic Genius of Statistics | p. 317 |
Carrying Out an Analysis of Variance | p. 319 |
Hypothesis Testing with the Analysis of Variance | p. 327 |
Assumptions in the Analysis of Variance | p. 331 |
Planned Contrasts | p. 334 |
Post Hoc Comparisons | p. 337 |
Effect Size and Power for the Analysis of Variance | p. 339 |
Controversy: Omnibus Tests versus Planned Contrasts | p. 343 |
Analyses of Variance in Research Articles | p. 344 |
Advanced Topic: The Structural Model in the Analysis of Variance | p. 345 |
Principles of the Structural Model | p. 345 |
Summary | p. 351 |
Key Terms | p. 352 |
Example Worked-Out Problems | p. 353 |
Practice Problems | p. 357 |
Using SPSS | p. 364 |
Chapter Notes | p. 368 |
Factorial Analysis of Variance | p. 370 |
Basic Logic of Factorial Designs and Interaction Effects | p. 371 |
Recognizing and Interpreting Interaction Effects | p. 376 |
Basic Logic of the Two-Way Analysis of Variance | p. 386 |
Personality and Situational Influences on Behavior: An Interaction Effect | p. 387 |
Assumptions in the Factorial Analysis of Variance | p. 389 |
Extensions and Special Cases of the Analysis of Variance | p. 389 |
Controversy: Dichotomizing Numeric Variables | p. 391 |
Factorial Analysis of Variance in Research Articles | p. 393 |
Advanced Topic: Figuring a Two-Way Analysis of Variance | p. 395 |
Advanced Topic: Power and Effect Size in the Factorial Analysis of Variance | p. 406 |
Summary | p. 410 |
Key Terms | p. 411 |
Example Worked-Out Problems | p. 412 |
Practice Problems | p. 415 |
Using SPSS | p. 426 |
Chapter Notes | p. 431 |
Correlation | p. 432 |
Graphing Correlations: The Scatter Diagram | p. 434 |
Patterns of Correlation | p. 437 |
The Correlation Coefficient | p. 443 |
Galton: Gentleman Genius | p. 446 |
Significance of a Correlation Coefficient | p. 452 |
Correlation and Causality | p. 456 |
Issues in Interpreting the Correlation Coefficient | p. 458 |
Illusory Correlation: When You Know Perfectly Well That If It's Big, It's Fat-and You Are Perfectly Wrong | p. 460 |
Effect Size and Power for the Correlation Coefficient | p. 464 |
Controversy: What Is a Large Correlation? | p. 466 |
Correlation in Research Articles | p. 467 |
Summary | p. 469 |
Key Terms | p. 471 |
Example Worked-Out Problems | p. 471 |
Practice Problems | p. 474 |
Using SPSS | p. 482 |
Chapter Notes | p. 485 |
Prediction | p. 487 |
Predictor (X) and Criterion (Y) Variables | p. 488 |
The Linear Prediction Rule | p. 488 |
The Regression Line | p. 492 |
Finding the Best Linear Prediction Rule | p. 496 |
The Least Squared Error Principle | p. 498 |
Issues in Prediction | p. 503 |
Multiple Regression | p. 506 |
Limitations of Prediction | p. 508 |
Controversy: Unstandardized and Standardized Regression Coefficients; Comparing Predictors | p. 509 |
Clinical versus Statistical Prediction | p. 510 |
Prediction in Research Articles | p. 511 |
Advanced Topic: Error and Proportionate Reduction in Error | p. 514 |
Summary | p. 518 |
Key Terms | p. 519 |
Example Worked-Out Problems | p. 519 |
Practice Problems | p. 524 |
Using SPSS | p. 532 |
Chapter Notes | p. 535 |
Chi-Square Tests | p. 536 |
Karl Pearson, Inventor of Chi-Square and Center of Controversy | p. 537 |
The Chi-Square Statistic and the Chi-Square Test for Goodness of Fit | p. 538 |
The Chi-Square Test for Independence | p. 546 |
Assumptions for Chi-Square Tests | p. 554 |
Effect Size and Power for Chi-Square Tests for Independence | p. 554 |
Controversy: The Minimum Expected Frequency | p. 558 |
Chi-Square Tests in Research Articles | p. 559 |
Summary | p. 560 |
Key Terms | p. 561 |
Example Worked-Out Problems | p. 561 |
Practice Problems | p. 565 |
Using SPSS | p. 572 |
Chapter Notes | p. 576 |
Strategies When Population Distributions Are Not Normal: Data Transformations and Rank-Order Tests | p. 577 |
Assumptions in the Standard Hypothesis-Testing Procedures | p. 578 |
Data Transformations | p. 580 |
Rank-Order Tests | p. 585 |
Comparison of Methods | p. 589 |
Controversy: Computer-Intensive Methods | p. 591 |
Where Do Random Numbers Come From? | p. 594 |
Data Transformations and Rank-Order Tests in Research Articles | p. 595 |
Summary | p. 596 |
Key Terms | p. 597 |
Example Worked-Out Problems | p. 597 |
Practice Problems | p. 597 |
Using SPSS | p. 602 |
Chapter Notes | p. 609 |
The General Linear Model and Making Sense of Advanced Statistical Procedures in Research Articles | p. 611 |
The General Linear Model | p. 612 |
Two Women Make a Point About Gender and Statistics | p. 616 |
Partial Correlation | p. 617 |
Reliability | p. 618 |
Multilevel Modeling | p. 620 |
Factor Analysis | p. 622 |
Causal Modeling | p. 625 |
The Golden Age of Statistics: Four Guys Around London | p. 627 |
Procedures That Compare Groups | p. 634 |
Analysis of Covariance (ANCOVA) | p. 634 |
Multivariate Analysis of Variance (MANOVA) and Multivariate Analysis of Covariance (MANCOVA) | p. 635 |
Overview of Statistical Techniques | p. 636 |
Controversy: Should Statistics Be Controversial? | p. 637 |
The Forced Partnership of Fisher and Pearson | p. 638 |
How to Read Results Using Unfamiliar Statistical Techniques | p. 639 |
Summary | p. 641 |
Key Terms | p. 642 |
Practice Problems | p. 642 |
Using SPSS | p. 654 |
Chapter Notes | p. 662 |
Tables | p. 664 |
Answers to Set I Practice Problems | p. 673 |
Glossary | p. 701 |
Glossary of Symbols | p. 708 |
References | p. 710 |
Index | p. 719 |
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