Intro
Preface
Contents
Chapter 1: Descriptive Statistics and Discrete Probability Distributions
1.1 Introduction
1.2 Definitions
1.3 Statistical Measures and the Display of Data
1.3.1 Histograms
1.3.2 Sample Median and Quartiles
1.3.3 Sample Mean and the Expected Value
1.3.4 Sample Variance
1.3.5 Probability Mass Function
1.3.6 Independent Random Variables
1.3.7 Unbiased Variance
1.4 Binomial and Poisson Distributions
1.4.1 Binomial Distribution
1.4.2 Poisson Distribution
1.5 Definitions Regarding Measurements
1.6 Exercises

Chapter 2: Continuous Probability Distributions, Confidence Intervals, and Hypothesis Testing
2.1 Introduction
2.2 Continuous Probability Distributions
2.2.1 Introduction
2.2.2 Definitions Using Continuous Probability Distributions
2.3 Normal Distribution
2.3.1 Normal Distribution
2.3.2 Combining Independent Normally Distributed Random Variables
2.3.3 Probability Plots for the Normal Distribution
2.3.4 Central Limit Theorem
2.3.5 Lognormal Distribution
2.4 Chi Square Distribution
2.5 Student t Distribution
2.6 Differences in the Means
2.6.1 Paired Samples

2.7 f Distribution
2.8 Weibull Distribution
2.9 Hypothesis Testing
2.9.1 Introduction
2.9.2 p-Value
2.9.3 Examples of Hypothesis Testing
2.9.4 Type I and Type II Errors
2.10 Exercises
Reference
Chapter 3: Regression Analysis and the Analysis of Variance
3.1 Introduction
3.2 Simple Linear Regression and the Analysis of Variance
3.2.1 Simple Linear Regression
3.2.2 Analysis of Variance (ANOVA)
3.2.3 Analysis of Residuals
3.3 Multiple Linear Regression
3.4 Exercises
Chapter 4: Experimental Design
4.1 Introduction

4.2 One-Factor Analysis of Variance
4.3 Randomized Complete Block Design
4.4 Two Factor Experiment
4.5 2k-Factorial Experiments
4.6 Exercises
Appendix A: Moment Generating Function
A.1 Moment Generating Function
A.2 Moment Generating Function of the Chi Square Distribution
A.3 Independence of Mean and Variance for Normally Distributed Independent Random Variables
Bibliography
Internet
Index