# EBook/Print versions

*Note: current version of this book can be found at http://wiki.stat.ucla.edu/socr/index.php/EBook*

## Contents

- 1 Table of contents
- 1.1 Preface
- 1.2 Chapter I: Introduction to Statistics
- 1.3 Chapter II: Describing, Exploring, and Comparing Data
- 1.4 Chapter III: Probability
- 1.5 Chapter IV: Probability Distributions
- 1.6 Chapter V: Normal Probability Distribution
- 1.7 Chapter VI: Relations Between Distributions
- 1.8 Chapter VII: Point and Interval Estimates
- 1.9 Chapter VIII: Hypothesis Testing
- 1.10 Chapter IX: Inferences From Two Samples
- 1.11 Chapter X: Correlation and Regression
- 1.12 Chapter XI: Analysis of Variance (ANOVA)
- 1.13 Chapter XII: Non-Parametric Inference
- 1.14 Chapter XIII: Multinomial Experiments and Contingency Tables
- 1.15 Additional EBook Chapters (under Development)

- 2 Format
- 3 Learning and Instructional Usage
- 4 The Nature of Data and Variation
- 5 Uses and Abuses of Statistics
- 6 Design of Experiments
- 7 Statistics with Tools (Calculators and Computers)
- 8 Types of Data
- 9 Summarizing Data with Frequency Tables
- 10 Pictures of Data
- 11 Measures of Central Tendency
- 12 Measures of Variation
- 13 Measures of Shape
- 14 Statistics
- 15 Graphs and Exploratory Data Analysis
- 16 Fundamentals
- 17 Rules for Computing Probabilities
- 18 Probabilities Through Simulations
- 19 Counting
- 20 Random Variables
- 21 Expectation (Mean) and Variance
- 22 Bernoulli and Binomial Experiments
- 23 Multinomial Experiments
- 24 Geometric, Hypergeometric and Negative Binomial
- 25 Poisson Distribution
- 26 The Standard Normal Distribution
- 27 Nonstandard Normal Distribution: Finding Probabilities
- 28 Nonstandard Normal Distribution: Finding Scores (Critical Values)
- 29 The Central Limit Theorem
- 30 Law of Large Numbers
- 31 Normal Distribution as Approximation to Binomial Distribution
- 32 Poisson Approximation to Binomial Distribution
- 33 Binomial Approximation to HyperGeometric
- 34 Normal Approximation to Poisson
- 35 Estimating a Population Mean: Large Samples
- 36 Estimating a Population Mean: Small Samples
- 37 Student's T distribution
- 38 Estimating a Population Proportion
- 39 Estimating a Population Variance
- 40 Fundamentals of Hypothesis Testing
- 41 Testing a Claim about a Mean: Large Samples
- 42 Testing a Claim about a Mean: Small Samples
- 43 Testing a Claim about a Proportion
- 44 Testing a Claim about a Standard Deviation or Variance
- 45 Inferences About Two Means: Dependent Samples
- 46 Inferences About Two Means: Independent Samples
- 47 Comparing Two Variances
- 48 Inferences about Two Proportions
- 49 Correlation
- 50 Regression
- 51 Variation and Prediction Intervals
- 52 Multiple Regression
- 53 One-Way ANOVA
- 54 Two-Way ANOVA
- 55 Differences of Medians (Centers) of Two Paired Samples
- 56 Differences of Medians (Centers) of Two Independent Samples
- 57 Differences of Proportions of Two Samples
- 58 Differences of Means of Several Independent Samples
- 59 Differences of Variances of Two Independent Samples
- 60 Multinomial Experiments: Goodness-of-Fit
- 61 Contingency Tables: Independence and Homogeneity

# Table of contents

## Preface

## Chapter I: Introduction to Statistics

- The Nature of Data and Variation
- Uses and Abuses of Statistics
- Design of Experiments
- Statistics with Tools (Calculators and Computers)

## Chapter II: Describing, Exploring, and Comparing Data

- Types of Data
- Summarizing Data with Frequency Tables
- Pictures of Data
- Measures of Central Tendency
- Measures of Variation
- Measures of Shape
- Statistics
- EBook/Graphs and Exploratory Data Analysis

## Chapter III: Probability

## Chapter IV: Probability Distributions

- Random Variables
- Expectation (Mean) and Variance
- Bernoulli and Binomial Experiments
- Multinomial Experiments
- Geometric, Hypergeometric and Negative Binomial
- Poisson Distribution

## Chapter V: Normal Probability Distribution

- The Standard Normal Distribution
- Nonstandard Normal Distribution: Finding Probabilities
- Nonstandard Normal Distribution: Finding Scores (Critical Values)

## Chapter VI: Relations Between Distributions

- The Central Limit Theorem
- Law of Large Numbers
- Normal Distribution as Approximation to Binomial Distribution
- Poisson Approximation to Binomial Distribution
- Binomial Approximation to HyperGeometric
- Normal Approximation to Poisson

## Chapter VII: Point and Interval Estimates

- Estimating a Population Mean: Large Samples
- Estimating a Population Mean: Small Samples
- Student's T distribution
- Estimating a Population Proportion
- Estimating a Population Variance

## Chapter VIII: Hypothesis Testing

- Fundamentals of Hypothesis Testing
- Testing a Claim about a Mean: Large Samples
- Testing a Claim about a Mean: Small Samples
- Testing a Claim about a Proportion
- Testing a Claim about a Standard Deviation or Variance

## Chapter IX: Inferences From Two Samples

- Inferences About Two Means: Dependent Samples
- Inferences About Two Means: Independent Samples
- Comparing Two Variances
- Inferences about Two Proportions

## Chapter X: Correlation and Regression

## Chapter XI: Analysis of Variance (ANOVA)

## Chapter XII: Non-Parametric Inference

- Differences of Medians (Centers) of Two Paired Samples
- Differences of Medians (Centers) of Two Independent Samples
- Differences of Proportions of Two Samples
- Differences of Means of Several Independent Samples
- Differences of Variances of Two Independent Samples

## Chapter XIII: Multinomial Experiments and Contingency Tables

## Additional EBook Chapters (under Development)

# Format

# Learning and Instructional Usage

EBook/Learning and Instructional Usage

# The Nature of Data and Variation

EBook/The Nature of Data and Variation

# Uses and Abuses of Statistics

EBook/Uses and Abuses of Statistics

# Design of Experiments

# Statistics with Tools (Calculators and Computers)

EBook/Statistics with Tools (Calculators and Computers)

# Types of Data

# Summarizing Data with Frequency Tables

EBook/Summarizing Data with Frequency Tables

# Pictures of Data

# Measures of Central Tendency

EBook/Measures of Central Tendency

# Measures of Variation

# Measures of Shape

# Statistics

# Graphs and Exploratory Data Analysis

EBook/Graphs and Exploratory Data Analysis

# Fundamentals

# Rules for Computing Probabilities

EBook/Rules for Computing Probabilities

# Probabilities Through Simulations

EBook/Probabilities Through Simulations

# Counting

# Random Variables

# Expectation (Mean) and Variance

EBook/Expectation (Mean) and Variance

# Bernoulli and Binomial Experiments

EBook/Bernoulli and Binomial Experiments

# Multinomial Experiments

# Geometric, Hypergeometric and Negative Binomial

EBook/Geometric, Hypergeometric and Negative Binomial

# Poisson Distribution

# The Standard Normal Distribution

EBook/The Standard Normal Distribution

# Nonstandard Normal Distribution: Finding Probabilities

EBook/Nonstandard Normal Distribution: Finding Probabilities

# Nonstandard Normal Distribution: Finding Scores (Critical Values)

EBook/Nonstandard Normal Distribution: Finding Scores (Critical Values)

# The Central Limit Theorem

EBook/The Central Limit Theorem

# Law of Large Numbers

# Normal Distribution as Approximation to Binomial Distribution

EBook/Normal Distribution as Approximation to Binomial Distribution

# Poisson Approximation to Binomial Distribution

EBook/Poisson Approximation to Binomial Distribution

# Binomial Approximation to HyperGeometric

EBook/Binomial Approximation to HyperGeometric

# Normal Approximation to Poisson

EBook/Normal Approximation to Poisson

# Estimating a Population Mean: Large Samples

EBook/Estimating a Population Mean: Large Samples

# Estimating a Population Mean: Small Samples

EBook/Estimating a Population Mean: Small Samples

# Student's T distribution

EBook/Student's T distribution

# Estimating a Population Proportion

EBook/Estimating a Population Proportion

# Estimating a Population Variance

EBook/Estimating a Population Variance

# Fundamentals of Hypothesis Testing

EBook/Fundamentals of Hypothesis Testing

# Testing a Claim about a Mean: Large Samples

EBook/Testing a Claim about a Mean: Large Samples

# Testing a Claim about a Mean: Small Samples

EBook/Testing a Claim about a Mean: Small Samples

# Testing a Claim about a Proportion

EBook/Testing a Claim about a Proportion

# Testing a Claim about a Standard Deviation or Variance

EBook/Testing a Claim about a Standard Deviation or Variance

# Inferences About Two Means: Dependent Samples

EBook/Inferences About Two Means: Dependent Samples

# Inferences About Two Means: Independent Samples

EBook/ Inferences About Two Means: Independent Samples

# Comparing Two Variances

EBook/ Comparing Two Variances

# Inferences about Two Proportions

EBook/Inferences about Two Proportions

# Correlation

# Regression

# Variation and Prediction Intervals

EBook/Variation and Prediction Intervals

# Multiple Regression

# One-Way ANOVA

# Two-Way ANOVA

# Differences of Medians (Centers) of Two Paired Samples

EBook/Differences of Medians (Centers) of Two Paired Samples

# Differences of Medians (Centers) of Two Independent Samples

EBook/Differences of Medians (Centers) of Two Independent Samples

# Differences of Proportions of Two Samples

EBook/Differences of Proportions of Two Samples

# Differences of Means of Several Independent Samples

EBook/Differences of Means of Several Independent Samples

# Differences of Variances of Two Independent Samples

EBook/Differences of Variances of Two Independent Samples

# Multinomial Experiments: Goodness-of-Fit

EBook/Multinomial Experiments: Goodness-of-Fit