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Probability and Statistical Inference Book 9th Ed Hogg Tanis Zimmerman
US $22.99
ApproximatelyRM 97.27
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“A little separation at spine when you open front cover, but fully intact. Overall very nice.”
Good
A book that has been read but is in good condition. Very minimal damage to the cover including scuff marks, but no holes or tears. The dust jacket for hard covers may not be included. Binding has minimal wear. The majority of pages are undamaged with minimal creasing or tearing, minimal pencil underlining of text, no highlighting of text, no writing in margins. No missing pages.
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Located in: La Grange Park, Illinois, United States
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eBay item number:136055516766
Item specifics
- Condition
- Good
- Seller Notes
- “A little separation at spine when you open front cover, but fully intact. Overall very nice.”
- Book Title
- Probability and Statistical Inference Hardcover
- ISBN
- 9780321923271
About this product
Product Identifiers
Publisher
Pearson Education
ISBN-10
0321923278
ISBN-13
9780321923271
eBay Product ID (ePID)
177666411
Product Key Features
Number of Pages
552 Pages
Publication Name
Probability and Statistical Inference
Language
English
Publication Year
2013
Subject
Probability & Statistics / General
Type
Textbook
Subject Area
Mathematics
Format
Hardcover
Dimensions
Item Height
1.1 in
Item Weight
42.4 Oz
Item Length
10.1 in
Item Width
8.3 in
Additional Product Features
Edition Number
9
Intended Audience
College Audience
Table Of Content
Preface Prologue 1. Probability 1.1 Properties of Probability 1.2 Methods of Enumeration 1.3 Conditional Probability 1.4 Independent Events 1.5 Bayes'' Theorem 2. Discrete Distributions 2.1 Random Variables of the Discrete Type 2.2 Mathematical Expectation 2.3 Special Mathematical Expectations 2.4 The Binomial Distribution 2.5 The Negative Binomial Distribution 2.6 The Poisson Distribution 3. Continuous Distributions 3.1 Random Variables of the Continuous Type 3.2 The Exponential, Gamma, and Chi-Square Distributions 3.3 The Normal Distribution 3.4 Additional Models 4. Bivariate Distributions 4.1 Bivariate Distributions of the Discrete Type 4.2 The Correlation Coe±cient 4.3 Conditional Distributions 4.4 Bivariate Distributions of the Continuous Type 4.5 The Bivariate Normal Distribution 5. Distributions of Functions of Random Variables 5.1 Functions of One Random Variable 5.2 Transformations of Two Random Variables 5.3 Several Random Variables 5.4 The Moment-Generating Function Technique 5.5 Random Functions Associated with Normal Distributions 5.6 The Central Limit Theorem 5.7 Approximations for Discrete Distributions 5.8 Chebyshev''s Inequality and Convergence in Probability 5.9 Limiting Moment-Generating Functions 6. Point Estimation 6.1 Descriptive Statistics 6.2 Exploratory Data Analysis 6.3 Order Statistics 6.4 Maximum Likelihood Estimation 6.5 A Simple Regression Problem 6.6 Asymptotic Distributions of Maximum Likelihood Estimators 6.7 Su±cient Statistics 6.8 Bayesian Estimation 6.9 More Bayesian Concepts 7. Interval Estimation 7.1 Confidence Intervals for Means 7.2 Confidence Intervals for the Di®erence of Two Means 7.3 Confidence Intervals for Proportions 7.4 Sample Size 7.5 Distribution-Free Confidence Intervals for Percentiles 7.6 More Regression 7.7 Resampling Methods 8. Tests of Statistical Hypotheses 8.1 Tests about One Mean 8.2 Tests of the Equality of Two Means 8.3 Tests about Proportions 8.4 The Wilcoxon Tests 8.5 Power of a Statistical Test 8.6 Best Critical Regions 8.7 Likelihood Ratio Tests 9. More Tests 9.1 Chi-Square Goodness-of-Fit Tests 9.2 Contingency Tables 9.3 One-Factor Analysis of Variance 9.4 Two-Way Analysis of Variance 9.5 General Factorial and 2k Factorial Designs 9.6 Tests Concerning Regression and Correlation 9.7 Statistical Quality Control Epilogue A. References B. Tables C. Answers to Odd-Numbered Exercises D. Review of Selected Mathematical Techniques Index
Synopsis
Normal 0 false false false Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts., Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts., Normal 0 false false false Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts. KEY TOPICS: Probability; Discrete Distributions; Continuous Distributions; Bivariate Distributions; Distributions of Functions of Random Variables; Point Estimation; Interval Estimation; Tests of Statistical Hypotheses; More Tests MARKET: For all readers interested in probability and statistical interference., For a one- or two-semester course; calculus background presumed, no previous study of probability or statistics is required. Written by three veteran statisticians, this applied introduction to probability and statistics emphasizes the existence of variation in almost every process, and how the study of probability and statistics helps us understand this variation. Designed for students with a background in calculus, this book continues to reinforce basic mathematical concepts with numerous real-world examples and applications to illustrate the relevance of key concepts.
LC Classification Number
QA273.H694 2015
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