Logo - springer
Slogan - springer

Statistics - Statistical Theory and Methods | Exact Statistical Methods for Data Analysis

Exact Statistical Methods for Data Analysis

Weerahandi, Samaradasa

Softcover reprint of the original 1st ed. 1995, XIV, 329 p.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 

ISBN 978-1-4612-0825-9

digitally watermarked, no DRM

The eBook version of this title will be available soon


learn more about Springer eBooks

add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$119.00

(net) price for USA

ISBN 978-0-387-40621-3

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • About this book

Now available in paperback.

Content Level » Research

Keywords » data analysis

Related subjects » Probability Theory and Stochastic Processes - Statistical Theory and Methods

Table of contents 

1 Preliminary Notions.- 1.1 Introduction.- 1.2 Sufficiency.- 1.3 Complete Sufficient Statistics.- 1.4 Exponential Families of Distributions.- 1.5 Invariance.- 1.6 Maximum Likelihood Estimation.- 1.7 Unbiased Estimation.- 1.8 Least Squares Estimation.- 1.9 Interval Estimation.- Exercises.- 2 Notions in significance testing of hypotheses.- 2.1 Introduction.- 2.2 Test Statistics and Test Variables.- 2.3 Definition of p-Value.- 2.4 Generalized Likelihood Ratio Method.- 2.5 Invariance in Significance Testing.- 2.6 Unbiasedness and Similarity.- 2.7 Interval Estimation and Fixed-Level Testing.- Exercises.- 3 Review of Special Distributions.- 3.1 Poisson and Binomial Distributions.- 3.2 Point Estimation and Interval Estimation.- 3.3 Significance Testing of Parameters.- 3.4 Bayesian Inference.- 3.5 The Normal Distribution.- 3.6 Inferences About the Mean.- 3.7 Inferences About the Variance.- 3.8 Quantiles of a Normal Distribution.- 3.9 Conjugate Prior and Posterior Distributions.- 3.10 Bayesian Inference About the Mean and the Variance.- Exercises.- 4 Exact Nonparametric Methods.- 4.1 Introduction.- 4.2 The Sign Test.- 4.3 The Signed Rank Test and the Permutation Test.- 4.4 The Rank Sum Test and Allied Tests.- 4.5 Comparing k Populations.- 4.6 Contingency Tables.- 4.7 Testing the Independence of Criteria of Classification.- 4.8 Testing the Homogeneity of Populations.- Exercises.- 5 Generalized p-Values.- 5.1 Introduction.- 5.2 Generalized Test Variables.- 5.3 Definition of Generalized p-Values.- 5.4 Frequency Interpretations and Generalized Fixed-Level Tests.- 5.5 Invariance.- 5.6 Comparing the Means of Two Exponential Distributions.- 5.7 Unbiasedness and Similarity.- 5.7 Comparing the Means of an Exponential Distribution and a Normal Distribution.- Exercises.- 6 Generalized Confidence Intervals.- 6.1 Introduction.- 6.2 Generalized Definitions.- 6.3 Frequency Interpretations and Repeated Sampling Properties.- 6.4 Invariance in Interval Estimation.- 6.5 Interval Estimation of the Difference Between Two Exponential Means.- 6.6 Similarity in Interval Estimation.- 6.7 Generalized Confidence Intervals Based on p-Values.- 6.8 Resolving an Undesirable Feature of Confidence Intervals.- 6.9 Bayesian and Conditional Confidence Intervals.- Exercises.- 7 Comparing Two Normal Populations.- 7.1 Introduction.- 7.2 Comparing the Means when the Variances are Equal.- 7.3 Solving the Behrens-Fisher Problem.- 7.4 Inferences About the Ratio of Two Variances.- 7.5 Inferences About the Difference in Two Variances.- 7.6 Bayesian Inference.- 7.7 Inferences About the Reliability Parameter.- 7.8 The Case of Known Stress Distribution.- Exercises.- 8 Analysis of Variance.- 8.1 Introduction.- 8.2 One-way Layout.- 8.3 Testing the Equality of Means.- 8.4 ANOVA with Unequal Error Variances.- 8.5 Multiple Comparisons.- 8.6 Testing the Equality of Variances.- 8.7 Two-way ANOVA without Replications.- 8.8 ANOVA in a Balanced Two-way Layout with Replications.- 8.9 Two-way ANOVA under Heteroscedasticity.- Exercises.- 9 Mixed Models.- 9.1 Introduction.- 9.2 One-way Layout.- 9.3 Testing Variance Components.- 9.4 Confidence Intervals.- 9.5 Two-way Layout.- 9.6 Comparing Variance Components.- Exercises.- 10 Regression.- 10.1 Introduction.- 10.2 Simple Linear Regression Model.- 10.3. Inferences about Parameters of the Simple Regression Model.- 10.3 Multiple Linear Regression.- 10.4 Distributions of Estimators and Significance Tests.- 10.5 Comparing Two Regressions with Equal Variances.- 10.6 Comparing Regressions without Common Parameters.- 10.7 Comparison of Two General Models.- Exercises.- Appendix A.- Elements of Bayesian Inference.- A.1 Introduction.- A.2 The Prior Distribution.- A.3 The Posterior Distribution.- A.4 Bayes Estimators.- A.5 Bayesian Interval Estimation.- A.6 Bayesian Hypothesis Testing.- Appendix B Technical Arguments.- References.

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistical Theory and Methods.

Additional information