To the Teacher |
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vi | |
Media and Supplements |
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xi | |
Acknowledgments |
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xiii | |
To the Student |
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xvi | |
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Chapter 0 What Is a Statistical Model? |
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1 | (20) |
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2 | (3) |
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5 | (16) |
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Chapter 1 Simple Linear Regression |
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21 | (38) |
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1.1 The Simple Linear Regression Model |
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22 | (5) |
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1.2 Conditions for a Simple Linear Model |
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27 | (2) |
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29 | (5) |
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1.4 Transformations/Reexpressions |
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34 | (9) |
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1.5 Outliers and Influential Points |
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43 | (16) |
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Chapter 2 Inference for Simple Linear Regression |
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59 | (28) |
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2.1 Inference for Regression Slope |
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60 | (4) |
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2.2 Partitioning Variability---ANOVA |
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64 | (3) |
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2.3 Regression and Correlation |
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67 | (3) |
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2.4 Intervals for Predictions |
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70 | (2) |
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2.5 Case Study: Butterfly Wings |
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72 | (15) |
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Chapter 3 Multiple Regression |
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87 | (66) |
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3.1 Multiple Linear Regression Model |
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90 | (2) |
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3.2 Assessing a Multiple Regression Model |
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92 | (6) |
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3.3 Comparing Two Regression Lines |
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98 | (9) |
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3.4 New Predictors from Old |
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107 | (14) |
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3.5 Correlated Predictors |
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121 | (6) |
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3.6 Testing Subsets of Predictors |
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127 | (5) |
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3.7 Case Study: Predicting in Retail Clothing |
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132 | (21) |
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Chapter 4 Additional Topics in Regression |
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153 | (44) |
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4.1 Topic: Added Variable Plots |
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154 | (2) |
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4.2 Topic: Techniques for Choosing Predictors |
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156 | (8) |
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4.3 Topic: Cross-validation |
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164 | (4) |
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4.4 Topic: Identifying Unusual Points in Regression |
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168 | (7) |
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4.5 Topic: Coding Categorical Predictors |
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175 | (6) |
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4.6 Topic: Randomization Test for a Relationship |
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181 | (3) |
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4.7 Topic: Bootstrap for Regression |
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184 | (13) |
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UNIT B Analysis of Variance |
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Chapter 5 One-way ANOVA and Randomized Experiments |
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197 | (60) |
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198 | (4) |
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5.2 The One-way Randomized Experiment and Its Observational Sibling |
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202 | (4) |
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206 | (10) |
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5.4 Formal Inference: Assessing and Using the Model |
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216 | (9) |
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5.5 How Big Is the Effect?: Confidence Intervals and Effect Sizes |
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225 | (6) |
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5.6 Using Plots to Help Choose a Scale for the Response |
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231 | (8) |
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5.7 Multiple Comparisons and Fisher's Least Significant Difference |
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239 | (3) |
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5.8 Case Study: Words with Friends |
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242 | (15) |
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Chapter 6 Blocking and Two-way ANOVA |
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257 | (42) |
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6.1 Choose: RCB Design and Its Observational Relatives |
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257 | (10) |
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6.2 Exploring Data from Block Designs |
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267 | (5) |
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6.3 Fitting the Model for a Block Design |
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272 | (5) |
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6.4 Assessing the Model for a Block Design |
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277 | (8) |
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6.5 Using the Model for a Block Design |
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285 | (14) |
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Chapter 7 ANOVA with interaction and Factorial Designs |
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299 | (44) |
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300 | (5) |
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7.2 Design: The Two-way Factorial Experiment |
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305 | (3) |
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7.3 Exploring Two-way Data |
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308 | (7) |
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7.4 Fitting a Two-way Balanced ANOVA Model |
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315 | (6) |
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7.5 Assessing Fit: Do We Need a Transformation? |
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321 | (1) |
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7.6 Using a Two-way ANOVA Model |
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322 | (21) |
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Chapter 8 Additional Topics in Analysis of Variance |
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343 | (70) |
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8.1 Topic: Levene's Test for Homogeneity of Variances |
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344 | (4) |
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8.2 Topic: Multiple Tests |
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348 | (5) |
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8.3 Topic: Comparisons and Contrasts |
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353 | (7) |
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8.4 Topic: Nonparametric Statistics |
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360 | (5) |
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8.5 Topic: Randomization F-Test |
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365 | (9) |
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8.6 Topic: Repeated Measures Designs and Datasets |
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374 | (5) |
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8.7 Topic: ANOVA and Regression with Indicators |
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379 | (10) |
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8.8 Topic: Analysis of Covariance |
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389 | (24) |
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8.9 Repeated Measures: Mixed Designs |
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8.10 Repeated Measures: Advanced Material |
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8.11 Randomization Testing for Repeated Measures |
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UNIT C Logistic Regression |
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Chapter 9 Logistic Regression |
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413 | (40) |
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9.1 Choosing a Logistic Regression Model |
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414 | (10) |
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9.2 Logistic Regression and Odds Ratios |
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424 | (6) |
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9.3 Assessing the Logistic Regression Model |
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430 | (7) |
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9.4 Formal Inference: Tests and Intervals |
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437 | (16) |
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Chapter 10 Multiple Logistic Regression |
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453 | (44) |
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454 | (2) |
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10.2 Choosing, Fitting, and Interpreting Models |
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456 | (9) |
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465 | (8) |
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10.4 Formal Inference: Tests and Intervals |
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473 | (8) |
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10.5 Case Study: Attractiveness and Fidelity |
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481 | (16) |
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Chapter 11 Additional Topics in Logistic Regression |
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497 | (42) |
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11.1 Topic: Fitting the Logistic Regression Model |
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498 | (4) |
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11.2 Topic: Assessing Logistic Regression Models |
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502 | (12) |
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11.3 Topic: Randomization Tests for Logistic Regression |
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514 | (2) |
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11.4 Topic: Analyzing Two-Way Tables with Logistic Regression |
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516 | (6) |
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11.5 Topic: Simpson's Paradox |
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522 | (17) |
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UNIT D Time Series Analysis |
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Chapter 12 Time Series Analysis |
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539 | (50) |
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540 | (11) |
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12.2 Measuring Dependence on Past Values: Autocorrelation |
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551 | (7) |
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558 | (13) |
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12.4 Case Study: Residual Oil |
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571 | (18) |
Answers to Selected Exercises |
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589 | (9) |
Notes and Data Sources |
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598 | (5) |
General Index |
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603 | (3) |
Dataset Index |
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606 | |