Preface |
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xi | |
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Preliminaries: How to Use This Book |
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1 | (16) |
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Statistics and the Behavioral Sciences |
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1 | (2) |
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Computing Statistics by Hand and Computer |
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3 | (9) |
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An Integrated Approach to Learning Statistics |
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12 | (5) |
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Getting Started: The Logic of Hypothesis Testing |
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17 | (14) |
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Statistics, Samples, and Populations |
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17 | (3) |
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Hypothesis Testing: An Introduction |
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20 | (4) |
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False Claims, Real Effects, and Power |
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24 | (6) |
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Why Discuss Inferential Before Descriptive Statistics? |
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30 | (1) |
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Inferring From a Sample: The Binomial Distribution |
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31 | (14) |
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The Binomial Distribution |
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31 | (8) |
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39 | (6) |
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Measuring Variables: Some Basic Vocabulary |
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45 | (8) |
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45 | (3) |
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Designing a Study: Independent and Dependent Variables |
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48 | (1) |
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Matching Study Designs with Statistical Procedures |
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49 | (4) |
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Describing a Sample: Basic Descriptive Statistics |
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53 | (18) |
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54 | (6) |
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60 | (3) |
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63 | (3) |
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66 | (5) |
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Describing a Sample: Graphical Techniques |
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71 | (12) |
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Principles of good design |
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72 | (1) |
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Graphical Techniques Explained |
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73 | (10) |
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Inferring From a Sample: The Normal and t Distributions |
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83 | (20) |
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The Normal Approximation for the Binomial |
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84 | (3) |
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87 | (4) |
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The Central Limit Theorem |
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91 | (1) |
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92 | (1) |
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93 | (5) |
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Ninety-Five Percent Confidence Intervals |
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98 | (5) |
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Accounting for Variance: A Single Predictor |
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103 | (14) |
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Simple Regression and Correlation |
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103 | (10) |
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What Accounting for Variance Means |
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113 | (4) |
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Bivariate Relations: The Regression and Correlation Coefficients |
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117 | (20) |
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Computing the Slope and the Y Intercept |
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119 | (5) |
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Computing the Correlation Coefficient |
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124 | (3) |
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Detecting Group Differences with a Binary Predictor |
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127 | (5) |
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Graphing the Regression Line |
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132 | (5) |
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Inferring From a Sample: The F Distribution |
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137 | (18) |
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Estimating Population Variance |
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137 | (3) |
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140 | (2) |
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142 | (7) |
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The Analysis of Variance: Two Independent Groups |
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149 | (3) |
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Assumptions of the F test |
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152 | (3) |
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Accounting for Variance: Multiple Predictors |
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155 | (26) |
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Multiple Regression and Correlation |
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156 | (10) |
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Significance Testing with Multiple Predictors |
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166 | (2) |
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Accounting for Unique Additional Variance |
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168 | (3) |
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Hierarchie MRC and the Analysis of Covariance |
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171 | (7) |
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178 | (3) |
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Single-Factor Between-Subjects Studies |
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181 | (20) |
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Coding Categorical Predictor Variables |
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182 | (12) |
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One-Way Analysis of Variance |
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194 | (3) |
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197 | (4) |
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Planned Comparisons, Post Hoc Tests, and Adjusted Means |
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201 | (22) |
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Organizing Stepwise Statistics |
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203 | (2) |
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205 | (1) |
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206 | (4) |
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Unequal Numbers of Subjects Per Group |
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210 | (2) |
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Adjusted Means and the Analysis of Covariance |
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212 | (11) |
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Studies With Multiple Between-Subjects Factors |
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223 | (22) |
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Between-Subjects Factorial Studies |
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224 | (9) |
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Significance Testing for Main Effects and Interactions |
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233 | (2) |
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Interpreting Significant Main Effects and Interactions |
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235 | (3) |
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Magnitude of Effects and Partial Eta Squared |
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238 | (7) |
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Single-Factor Within-Subjects Studies |
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245 | (24) |
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Within-Subjects or Repeated-Measures Factors |
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245 | (5) |
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Controlling Between-Subjects Variability |
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250 | (8) |
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Modifying the Source Table for Repeated Measures |
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258 | (8) |
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Assumptions of the Repeated Measure ANOVA |
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266 | (3) |
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Two-Factor Studies With Repeated Measures |
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269 | (20) |
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One Between- and One Within-Subjects Factor |
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269 | (9) |
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Two Within-Subjects Factors |
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278 | (6) |
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Explicating Interactions with Repeated Measures |
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284 | (2) |
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Generalizing to More Complex Designs |
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286 | (3) |
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Power, Pitfalls, and Practical Matters |
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289 | (12) |
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Pretest, Posttest: Repeated Measure Or Covariate? |
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289 | (6) |
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Power Analysis: How Many Subjects Are Enough? |
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295 | (6) |
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301 | (2) |
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Glossary of Symbols and Key Terms |
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303 | (6) |
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Appendix A: SAS exercises |
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309 | (16) |
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Appendix B: Answers to Selected Exercises |
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325 | (32) |
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Appendix C: Statistical Tables |
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A. Critical Values for the Binomial Distribution, P = 0.5 |
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345 | (2) |
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B. Areas Under the Normal Curve |
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347 | (3) |
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C. Critical Values for the t Distribution |
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350 | (1) |
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D.1 Critical Values for the F Distribution, α = .05 |
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351 | (1) |
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D.2 Critical Values for the F Distribution, α = .01 |
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352 | (1) |
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E.1 Distribution of the Studentized Range Statistic, α = .05 |
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353 | (1) |
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E.2 Distribution of the Studentized Range Statistic, α = .01 |
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354 | (1) |
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355 | (1) |
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356 | (1) |
Author Index |
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357 | (2) |
Subject Index |
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359 | |