Product Review
This innovative new introduction to Mathematical Statistics covers the important concept of estimation at a point much earlier (Chapter 2) than others on this subject. Applies mathematical statistics to topics such as insurance, Pap smear tests, estimating the number of whales in an ocean, fitting models, filling 12 ounce containers, environmental issues, and results in certain sporting events. Includes summaries of the most important aspects of discrete distributions, continuous distributions, confidence intervals, and tests of hypotheses. Provides computer applications for data analysis and also for theoretical solutions such as simulation and bootstrapping. A comprehensive reference for individuals who need to brush up on their knowledge of statistics.
- Preface
- 1. Probability
- 1.1 Basic Concepts
- 1.2 Methods of Enumeration
- 1.3 Conditional Probability
- 1.4 Independent Events
- 1.5 Bayes's Theorem
- Chapter One Comments
- 2. Discrete Distributions
- 2.1 Discrete Probability Distributions
- 2.2 Expectations
- 2.3 Special Discrete Distributions
- 2.4 Estimation
- 2.5 Linear Functions of Independent Random Variables
- 2.6 Multivariate Discrete Distributions
- Chapter Two Comments
- 3. Continuous Distributions
- 3.1 Descriptive Statistics and EDA
- 3.2 Continuous Probability Distributions
- 3.3 Special Continuous Distributions
- 3.4 The Normal Distribution
- 3.5 Estimation in the Continuous Case
- 3.6 The Central Limit Theorem
- 3.7 Approximations for Discrete Distributions
- Chapter Three Comemnts
- 4. Applications of Statistical Inference
- 4.1 Summary of Necessary Theoretical Results
- 4.2 Confidence Intervals Using X2 F,and T
- 4.3 Confidence Intervals and Tests of Hypotheses
- 4.4 Basic Tests Concerning One Parameter
- 4.5 Tests of the Equality of Two Parameters
- 4.6 Simple Linear Regression
- 4.7 More on Linear Regression
- 4.8 One-Factor Analysis of Variance
- 4.9 Distribution-Free Confidence and Tolerance Intervals
- 4.10 Chi-Square Goodness of Fit Tests
- 4.11 Contingency Tables
- Chapter Four Comments
- 5. Computer Oriented Techniques
- 5.1 Computation of Statistics
- 5.2 Computer Algebra Systems
- 5.3 Simulation
- 5.4 Resampling
- Chapter Five Comments
- 6. Some Sampling Distribution Theory
- 6.1 Moment-Generation Function Technique
- 6.2 M.G.F of Linear Functions
- 6.3 Limiting Moment-Generating Functions
- 6.4 Use of Order Statistics in Non-regular Cases
- Chapter Six Comments
