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Mathematical Statistics with Resampling and R.

By: Material type: TextTextSeries: New York Academy of Sciences SeriesPublisher: Newark : John Wiley & Sons, Incorporated, 2011Copyright date: ©2011Edition: 1st edDescription: 1 online resource (393 pages)Content type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781118518953
Subject(s): Genre/Form: Additional physical formats: Print version:: Mathematical Statistics with Resampling and RDDC classification:
  • 310
LOC classification:
  • QA278.8 .C45 2011
Online resources:
Contents:
Intro -- Half Title page -- Title page -- Copyright page -- Preface -- Acknowledgments -- Chapter 1: Data and Case Studies -- 1.1 Case Study: Flight Delays -- 1.2 Case Study: Birth Weights of Babies -- 1.3 Case Study: Verizon Repair Times -- 1.4 Sampling -- 1.5 Parameters and Statistics -- 1.6 Case Study: General Social Survey -- 1.7 Sample Surveys -- 1.8 Case Study: Beer and Hot Wings -- 1.9 Case Study: Black Spruce Seedlings -- 1.10 Studies -- 1.11 Exercises -- Chapter 2: Exploratory Data Analysis -- 2.1 Basic Plots -- 2.2 Numeric Summaries -- 2.3 Boxplots -- 2.4 Quantiles and Normal Quantile Plots -- 2.5 Empirical Cumulative Distribution Functions -- 2.6 Scatter Plots -- 2.7 Skewness and Kurtosis -- 2.8 Exercises -- Chapter 3: Hypothesis Testing -- 3.1 Introduction to Hypothesis Testing -- 3.2 Hypotheses -- 3.3 Permutation Tests -- 3.4 Contingency Tables -- 3.5 Chi-Square Test of Independence -- 3.6 Test of Homogeneity -- 3.7 Goodness-of-Fit: All Parameters Known -- 3.8 Goodness-of-Fit: Some Parameters Estimated -- 3.9 Exercises -- Chapter 4: Sampling Distributions -- 4.1 Sampling Distributions -- 4.2 Calculating Sampling Distributions -- 4.3 The Central Limit Theorem -- 4.4 Exercises -- Chapter 5: The Bootstrap -- 5.1 Introduction to the Bootstrap -- 5.2 The Plug-in Principle -- 5.3 Bootstrap Percentile Intervals -- 5.4 Two Sample Bootstrap -- 5.5 Other Statistics -- 5.6 Bias -- 5.7 Monte Carlo Sampling: The "Second Bootstrap Principle" -- 5.8 Accuracy of Bootstrap Distributions -- 5.9 How Many Bootstrap Samples are Needed? -- 5.10 Exercises -- Chapter 6: Estimation -- 6.1 Maximum Likelihood Estimation -- 6.2 Method of Moments -- 6.3 Properties of Estimators -- 6.4 Exercises -- Chapter 7: Classical Inference: Confidence Intervals -- 7.1 Confidence Intervals for Means -- 7.2 Confidence Intervals in General -- 7.3 One-Sided Confidence Intervals.
7.4 Confidence Intervals for Proportions -- 7.5 Bootstrap t Confidence Intervals -- 7.6 Exercises -- Chapter 8: Classical Inference: Hypothesis Testing -- 8.1 Hypothesis Tests for Means and Proportions -- 8.2 Type I and Type Ii Errors -- 8.3 More on Testing -- 8.4 Likelihood Ratio Tests -- 8.5 Exercises -- Chapter 9: Regression -- 9.1 Covariance -- 9.2 Correlation -- 9.3 Least-Squares Regression -- 9.4 The Simple Linear Model -- 9.5 Resampling Correlation and Regression -- 9.6 Logistic Regression -- 9.7 Exercises -- Chapter 10: Bayesian Methods -- 10.1 Bayes'Theorem -- 10.2 Binomial Data, Discrete Prior Distributions -- 10.3 Binomial Data, Continuous Prior Distributions -- 10.4 Continuous Data -- 10.5 Sequential Data -- 10.6 Exercises -- Chapter 11: Additional Topics -- 11.1 Smoothed Bootstrap -- 11.2 Parametric Bootstrap -- 11.3 The Delta Method -- 11.4 Stratified Sampling -- 11.5 Computational Issues in Bayesian Analysis -- 11.6 Monte Carlo Integration -- 11.7 Importance Sampling -- 11.8 Exercises -- Appendix A: Review of Probability -- A.1 Basic Probability -- A.2 Mean and Variance -- A.3 The Mean of A Sample of Random Variables -- A.4 The Law of Averages -- A.5 The Normal Distribution -- A.6 Sums of Normal Random Variables -- A.7 Higher Moments and the Moment Generating Function -- Appendix B: Probability Distributions -- B.1 The Bernoulli and Binomial Distributions -- B.2 The Multinomial Distribution -- B.3 The Geometric Distribution -- B.4 The Negative Binomial Distribution -- B.5 The Hypergeometric Distribution -- B.6 The Poisson Distribution -- B.7 The Uniform Distribution -- B.8 The Exponential Distribution -- B.9 The Gamma Distribution -- B.10 The Chi-Square Distribution -- B.11 The Student's t Distribution -- B.12 The Beta Distribution -- B.13 The F Distribution -- B.14 Exercises -- Appendix C: Distributions Quick Reference.
Solutions to Odd-Numbered Exercises -- Bibliography -- Index.
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Intro -- Half Title page -- Title page -- Copyright page -- Preface -- Acknowledgments -- Chapter 1: Data and Case Studies -- 1.1 Case Study: Flight Delays -- 1.2 Case Study: Birth Weights of Babies -- 1.3 Case Study: Verizon Repair Times -- 1.4 Sampling -- 1.5 Parameters and Statistics -- 1.6 Case Study: General Social Survey -- 1.7 Sample Surveys -- 1.8 Case Study: Beer and Hot Wings -- 1.9 Case Study: Black Spruce Seedlings -- 1.10 Studies -- 1.11 Exercises -- Chapter 2: Exploratory Data Analysis -- 2.1 Basic Plots -- 2.2 Numeric Summaries -- 2.3 Boxplots -- 2.4 Quantiles and Normal Quantile Plots -- 2.5 Empirical Cumulative Distribution Functions -- 2.6 Scatter Plots -- 2.7 Skewness and Kurtosis -- 2.8 Exercises -- Chapter 3: Hypothesis Testing -- 3.1 Introduction to Hypothesis Testing -- 3.2 Hypotheses -- 3.3 Permutation Tests -- 3.4 Contingency Tables -- 3.5 Chi-Square Test of Independence -- 3.6 Test of Homogeneity -- 3.7 Goodness-of-Fit: All Parameters Known -- 3.8 Goodness-of-Fit: Some Parameters Estimated -- 3.9 Exercises -- Chapter 4: Sampling Distributions -- 4.1 Sampling Distributions -- 4.2 Calculating Sampling Distributions -- 4.3 The Central Limit Theorem -- 4.4 Exercises -- Chapter 5: The Bootstrap -- 5.1 Introduction to the Bootstrap -- 5.2 The Plug-in Principle -- 5.3 Bootstrap Percentile Intervals -- 5.4 Two Sample Bootstrap -- 5.5 Other Statistics -- 5.6 Bias -- 5.7 Monte Carlo Sampling: The "Second Bootstrap Principle" -- 5.8 Accuracy of Bootstrap Distributions -- 5.9 How Many Bootstrap Samples are Needed? -- 5.10 Exercises -- Chapter 6: Estimation -- 6.1 Maximum Likelihood Estimation -- 6.2 Method of Moments -- 6.3 Properties of Estimators -- 6.4 Exercises -- Chapter 7: Classical Inference: Confidence Intervals -- 7.1 Confidence Intervals for Means -- 7.2 Confidence Intervals in General -- 7.3 One-Sided Confidence Intervals.

7.4 Confidence Intervals for Proportions -- 7.5 Bootstrap t Confidence Intervals -- 7.6 Exercises -- Chapter 8: Classical Inference: Hypothesis Testing -- 8.1 Hypothesis Tests for Means and Proportions -- 8.2 Type I and Type Ii Errors -- 8.3 More on Testing -- 8.4 Likelihood Ratio Tests -- 8.5 Exercises -- Chapter 9: Regression -- 9.1 Covariance -- 9.2 Correlation -- 9.3 Least-Squares Regression -- 9.4 The Simple Linear Model -- 9.5 Resampling Correlation and Regression -- 9.6 Logistic Regression -- 9.7 Exercises -- Chapter 10: Bayesian Methods -- 10.1 Bayes'Theorem -- 10.2 Binomial Data, Discrete Prior Distributions -- 10.3 Binomial Data, Continuous Prior Distributions -- 10.4 Continuous Data -- 10.5 Sequential Data -- 10.6 Exercises -- Chapter 11: Additional Topics -- 11.1 Smoothed Bootstrap -- 11.2 Parametric Bootstrap -- 11.3 The Delta Method -- 11.4 Stratified Sampling -- 11.5 Computational Issues in Bayesian Analysis -- 11.6 Monte Carlo Integration -- 11.7 Importance Sampling -- 11.8 Exercises -- Appendix A: Review of Probability -- A.1 Basic Probability -- A.2 Mean and Variance -- A.3 The Mean of A Sample of Random Variables -- A.4 The Law of Averages -- A.5 The Normal Distribution -- A.6 Sums of Normal Random Variables -- A.7 Higher Moments and the Moment Generating Function -- Appendix B: Probability Distributions -- B.1 The Bernoulli and Binomial Distributions -- B.2 The Multinomial Distribution -- B.3 The Geometric Distribution -- B.4 The Negative Binomial Distribution -- B.5 The Hypergeometric Distribution -- B.6 The Poisson Distribution -- B.7 The Uniform Distribution -- B.8 The Exponential Distribution -- B.9 The Gamma Distribution -- B.10 The Chi-Square Distribution -- B.11 The Student's t Distribution -- B.12 The Beta Distribution -- B.13 The F Distribution -- B.14 Exercises -- Appendix C: Distributions Quick Reference.

Solutions to Odd-Numbered Exercises -- Bibliography -- Index.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.

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