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1 Overview and Descriptive Statistics |
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1 | (48) |
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1.1 The Language of Statistics |
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1 | (8) |
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1.2 Graphical Methods in Descriptive Statistics |
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9 | (16) |
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25 | (7) |
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1.4 Measures of Variability |
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32 | (17) |
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43 | (6) |
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49 | (62) |
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2.1 Sample Spaces and Events |
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49 | (6) |
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2.2 Axioms, Interpretations, and Properties of Probability |
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55 | (11) |
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66 | (9) |
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2.4 Conditional Probability |
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75 | (12) |
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87 | (7) |
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2.6 Simulation of Random Events |
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94 | (17) |
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103 | (8) |
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3 Discrete Random Variables and Probability Distributions |
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111 | (78) |
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111 | (4) |
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3.2 Probability Distributions for Discrete Random Variables |
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115 | (11) |
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3.3 Expected Values of Discrete Random Variables |
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126 | (11) |
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3.4 Moments and Moment Generating Functions |
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137 | (7) |
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3.5 The Binomial Probability Distribution |
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144 | (12) |
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3.6 The Poisson Probability Distribution |
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156 | (8) |
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3.7 Other Discrete Distributions |
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164 | (9) |
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3.8 Simulation of Discrete Random Variables |
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173 | (16) |
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182 | (7) |
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4 Continuous Random Variables and Probability Distributions |
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189 | (88) |
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4.1 Probability Density Functions and Cumulative Distribution Functions |
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189 | (14) |
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4.2 Expected Values and Moment Generating Functions |
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203 | (10) |
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4.3 The Normal Distribution |
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213 | (17) |
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4.4 The Gamma Distribution and Its Relatives |
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230 | (9) |
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4.5 Other Continuous Distributions |
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239 | (8) |
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247 | (11) |
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4.7 Transformations of a Random Variable |
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258 | (5) |
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4.8 Simulation of Continuous Random Variables |
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263 | (14) |
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269 | (8) |
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5 Joint Probability Distributions and Their Applications |
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277 | (80) |
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5.1 Jointly Distributed Random Variables |
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277 | (17) |
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5.2 Expected Values, Covariance, and Correlation |
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294 | (9) |
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303 | (14) |
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5.4 Conditional Distributions and Conditional Expectation |
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317 | (13) |
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5.5 The Bivariate Normal Distribution |
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330 | (6) |
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5.6 Transformations of Multiple Random Variables |
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336 | (6) |
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342 | (15) |
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350 | (7) |
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6 Statistics and Sampling Distributions |
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357 | (40) |
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6.1 Statistics and Their Distributions |
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357 | (11) |
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6.2 The Distribution of Sample Totals, Means, and Proportions |
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368 | (12) |
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6.3 The Χ2, t and F Distributions |
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380 | (8) |
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6.4 Distributions Based on Normal Random Samples |
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388 | (9) |
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393 | (2) |
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Appendix: Proof of the Central Limit Theorem |
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395 | (2) |
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397 | (54) |
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7.1 Concepts and Criteria for Point Estimation |
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397 | (19) |
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7.2 The Methods of Moments and Maximum Likelihood |
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416 | (12) |
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428 | (8) |
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7.4 Information and Efficiency |
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436 | (15) |
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445 | (6) |
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8 Statistical Intervals Based on a Single Sample |
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451 | (50) |
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8.1 Basic Properties of Confidence Intervals |
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452 | (11) |
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8.2 The One-Sample t Interval and Its Relatives |
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463 | (12) |
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8.3 Intervals for a Population Proportion |
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475 | (6) |
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8.4 Confidence Intervals for the Population Variance and Standard Deviation |
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481 | (3) |
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8.5 Bootstrap Confidence Intervals |
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484 | (17) |
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494 | (7) |
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9 Tests of Hypotheses Based on a Single Sample |
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501 | (64) |
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9.1 Hypotheses and Test Procedures |
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501 | (11) |
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9.2 Tests About a Population Mean |
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512 | (14) |
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9.3 Tests About a Population Proportion |
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526 | (6) |
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532 | (10) |
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9.5 The Neyman-Pearson Lemma and Likelihood Ratio Tectc |
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542 | (11) |
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9.6 Further Aspects of Hypothesis Testing |
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553 | (12) |
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560 | (5) |
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10 Inferences Based on Two Samples |
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565 | (74) |
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10.1 The Two-Sample z Confidence Interval and Test |
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565 | (10) |
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10.2 The Two-Sample t Confidence Interval and Test |
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575 | (16) |
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10.3 Analysis of Paired Data |
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591 | (11) |
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10.4 Inferences About Two Population Proportions |
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602 | (9) |
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10.5 Inferences About Two Population Variances |
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611 | (6) |
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10.6 Inferences Using the Bootstrap and Permutation Methods |
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617 | (22) |
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630 | (9) |
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11 The Analysis of Variance |
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639 | (64) |
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640 | (13) |
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11.2 Multiple Comparisons in ANOVA |
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653 | (9) |
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11.3 More on Single-Factor ANOVA |
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662 | (10) |
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11.4 Two-Factor ANOVA without Replication |
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672 | (15) |
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11.5 Two-Factor ANOVA with Replication |
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687 | (16) |
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699 | (4) |
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12 Regression and Correlation |
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703 | (120) |
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12.1 The Simple Linear Regression Model |
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704 | (9) |
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12.2 Estimating Model Parameters |
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713 | (14) |
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12.3 Inferences About the Regression Coefficient β1 |
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727 | (10) |
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12.4 Inferences for the (Mean) Response |
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737 | (8) |
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745 | (12) |
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12.6 Investigating Model Adequacy: Residual Analysis |
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757 | (10) |
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12.7 Multiple Regression Analysis |
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767 | (16) |
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12.8 Quadratic, Interaction, and Indicator Terms |
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783 | (12) |
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12.9 Regression with Matrices |
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795 | (11) |
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12.10 Logistic Regression |
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806 | (17) |
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817 | (6) |
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823 | (32) |
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13.1 Goodness-of-Fit Tests |
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823 | (17) |
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13.2 Two-Way Contingency Tables |
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840 | (15) |
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851 | (4) |
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855 | (34) |
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14.1 Exact Inference for Population Quantiles |
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855 | (6) |
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14.2 One-Sample Rank-Based Inference |
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861 | (10) |
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14.3 Two-Sample Rank-Based Inference |
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871 | (8) |
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879 | (10) |
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886 | (3) |
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15 Introduction to Bayesian Estimation |
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889 | (14) |
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15.1 Prior and Posterior Distributions |
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889 | (7) |
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15.2 Bayesian Point and Interval Estimation |
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896 | (7) |
Appendix |
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903 | (23) |
Answers to Odd-Numbered Exercises |
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926 | (37) |
References |
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963 | (2) |
Index |
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965 | |