| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA990005468680203316 |
|
|
Autore |
SACHS, Lothar |
|
|
Titolo |
A guide to statistical methods and to pertinent literature = Literatur zur angewandten statistik / Lothar Sachs. - Berlin : Springer Verlag, 1986 |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
|
|
|
|
|
Collocazione |
|
DIP.TO SCIENZE ECONOMICHE - (SA) |
500 519.5 SAC |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
2. |
Record Nr. |
UNINA9910461263703321 |
|
|
Autore |
Chihara Laura <1957-> |
|
|
Titolo |
Mathematical statistics with resampling and R / / Laura Chihara, Tim Hesterberg |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Hoboken, New Jersey : , : Wiley, , 2011 |
|
©2011 |
|
|
|
|
|
|
|
|
|
ISBN |
|
1-118-62575-7 |
1-118-51895-0 |
|
|
|
|
|
|
|
|
Edizione |
[1st edition] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (723 p.) |
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Resampling (Statistics) |
Statistics |
Electronic books. |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Note generali |
|
Description based upon print version of record. |
|
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Nota di contenuto |
|
Cover; 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 Functions2.6 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 Bootstrap5.2 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 Intervals7.4 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 Distributions10.3 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 |
|
|
|
|
|
|
Sommario/riassunto |
|
This book bridges the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, Mathematical Statistics with Resampling and R utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling t |
|
|
|
|
|
|
|
| |