An Introduction to Mathematical Statistics and Its

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Artikelzustand
Neu: Neues, ungelesenes, ungebrauchtes Buch in makellosem Zustand ohne fehlende oder beschädigte ...
Topic
Statistics
ISBN
9780139223037
Kategorie

Über dieses Produkt

Product Information

For courses in Mathematical Statistics. Renowned for its high-quality, real-world case studies and examples, this highly structured text is designed to allow students with an established mathematics background to pursue a more rigorous, advanced treatment of probability and statistics. It shows HOW to use statistical methods, WHEN to use them, and reinforces the calculus that students have covered in previous courses. *Cover pages include a chart of densities, moments, and moment generating functions. *Additional simulations and Monte Carlo studies. *Minitab sections - At the end of chapters. *Delineates how one experimental design differs from another and the statistical consequences of those differences. *A complete Solutions Manual in response to user demand. *Uses case studies and practical worked-out examples to motivate statistical reasoning and demonstrate the application of statistical methods to a wide variety of real-world situations.

Product Identifiers

Publisher
Prentice Hall PTR
ISBN-10
0139223037
ISBN-13
9780139223037
eBay Product ID (ePID)
999965

Product Key Features

Publication Year
2000
Number of Pages
790 Pages
Language
English
Type
Textbook
Author
Richard J. Larsen, Morris L. Marx
Format
Hardcover

Dimensions

Length
9.4in
Height
1.3in
Width
7.2in
Weight
46.6 Oz

Additional Product Features

LCCN
00-025176
Edition Number
3
Group
College Audience
Dewey Edition
23
Publication Date
2000-06-07
Illustrated
Yes
Dewey Decimal
519.5
Lc Classification Number
Qa276.L314 2001
Table of Content
(NOTE: Each chapter except Ch. 1 begins with an Introduction.) 1. Introduction. A Brief History. Some Examples. A Chapter Summary. 2. Probability. Sample Spaces and the Algebra of Sets. The Probability Function. Discrete Probability Functions. Continuous Probability Functions. Conditional Probability. Independence. Repeated Independent Trials. Combinatorics. Combinatorial Probability. 3. Random Variables. The Probability Density Function. The Hypergeometric and Binomial Distributions. The Cumulative Distribution Function. Joint Densities. Independent Random Variables. Combining and Transforming Random Variables. Order Statistics. Conditional Densities. Expected Values. Properties of Expected Values. The Variance. Properties of Variances. Chebyshev's Inequality. Higher Moments. Moment-Generating Functions. Appendix 3.A.1: MINITAB Applications. 4. Special Distributions. The Poisson Distribution. The Normal Distribution. The Geometric Distribution. The Negative Binomial Distribution. The Gamma Distribution. Appendix 4.A.1: MINITAB Applications. Appendix 4.A.2: A Proof of the Central Limit Theorem. 5. Estimation. Estimating Parameters: The Method of Maximum Likelihood and the Method of Moments. Interval Estimation. Properties of Estimators. Minimum-Variance Estimators: The Cramer-Rao Lower Bound. Sufficiency. Consistency. Appendix 5.A.1: MINITAB Applications. 6. Hypothesis Testing. The Decision Rule. Testing Binomial Data-H 0: p = p 0 . Type I and Type II Errors. A Notion of Optimality: The Generalized Likelihood Ratio. 7. The Normal Distribution. Point Estimates for 'Šm and 'Šs2. The 'Šc2 Distribution; Inferences about 'Šs2. The F and t Distributions. Drawing Inferences about 'Šm. Appendix 7.A.1: MINITAB Applications. Appendix 7.A.2: Some Distribution Results for Y and S 2 . Appendix 7.A.3: A Proof of Theorem 7.3.5. A Proof That the One-Sample t Test Is a GLRT. 8. Types of Data: A Brief Overview. Classifying Data. 9. Two-Sample Problems. Testing H 0 : 'Šmx = 'ŠmY-The Two-Sample t Test. Testing H0: 'Šs2x = 'Šs2Y-The F Test. Binomial Data: Testing H 0 : px = py. Confidence Intervals for the Two-Sample Problem. Appendix 9.A.1: A Derivation of the Two-Sample t Test (A Proof of Theorem 9.2.2.). Appendix 9.A.2: Power Calculations for a Two-Sample t Test. Appendix 9.A.3: MINITAB Applications. 10. Goodness-of-Fit Tests. The Multinomial Distribution. Goodness-of-Fit Tests: All Parameters Known. Goodness-of-Fit Tests: Parameters Unknown. Contingency Tables. Appendix 10.A.1: MINITAB Applications. 11. Regression. The Method of Least Squares. The Linear Model. Covariance and Correlation. The Bivariate Normal Distribution. Appendix 11.A.1: MINITAB Applications. Appendix 11.A.2: A Proof of Theorem 11.3.3. 12. The Analysis of Variance. The F Test. Multiple Comparisons: Tukey's Method. Testing Subhypotheses with Orthogonal Contrasts. Data Transformations. Appendix 12.A.1: MINITAB Applications. Appendix 12.A.2: A Proof of Theorem 12.2.2. Appendix 12.A.3: The Distribution of When H1 Is True. 13. Randomized Block Designs. The F Test for a Randomized Block Design. The Paired t Test. Appendix 13.A.1: MINITAB Applications. 14. Nonparametric Statistics. The Sign Test. The Wilcoxon Signed Rank Test. The Kruskal-Wallis Test. The Friedman Test. Appendix 14.A.1: MINITAB Applications. Appendix: Statistical Tables. Answers to Selected Odd-Numbered Questions. Bibliography. Index.
Copyright Date
2001

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