# Statistics for Psychology (Study Guide and Computer Workbook) / Edition 3

ISBN-10: 0130447234

ISBN-13: 9780130447234

Pub. Date: 08/28/2002

Publisher: Pearson

The top-selling Statistics for Psychology, Fifth Edition, emphasizes meaning and concepts, not just symbols and numbers. Everything is explained in direct, simple language. Definitional formulas are used throughout to provide a concise symbolic summary of the logic of each particular procedure. Each procedure is taught both verbally and numerically-an important step

## Overview

The top-selling Statistics for Psychology, Fifth Edition, emphasizes meaning and concepts, not just symbols and numbers. Everything is explained in direct, simple language. Definitional formulas are used throughout to provide a concise symbolic summary of the logic of each particular procedure. Each procedure is taught both verbally and numerically-an important step in permanently establishing a concept in a student's mind. Thoroughly up to date and well written, Statistics for Psychology engages the reader and helps students understand statistics.

## Product Details

ISBN-13:
9780130447234
Publisher:
Pearson
Publication date:
08/28/2002
Edition description:
Older Edition

## Table of Contents

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

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