# Essential Statistics

• ### Chapter 1: Introduction

• Basic Definitions and Concepts
• Overview
• Presentation of Data
• ### Chapter 2: Descriptive Statistics

• Three Popular Data Displays
• Measures of Central Location
• Measures of Variability
• Relative Position of Data
• The Empirical Rule and Chebyshev’s Theorem
• ### Chapter 3: Basic Concepts of Probability

• Sample Spaces, Events, and Their Probabilities
• Complements, Intersections, and Unions
• Conditional Probability and Independent Events
• ### Chapter 4: Discrete Random Variables

• Random Variables
• Probability Distributions for Discrete Random Variables
• The Binomial Distribution
• ### Chapter 5: Continuous Random Variables

• Continuous Random Variables
• The Standard Normal Distribution
• Probability Computations for General Normal Random Variables
• Areas of Tails of Distributions
• ### Chapter 6: Sampling Distributions

• The Mean and Standard Deviation of the Sample Mean
• The Sampling Distribution of the Sample Mean
• The Sample Proportion
• ### Chapter 7: Estimation

• Large Sample Estimation of a Population Mean
• Small Sample Estimation of a Population Mean
• Large Sample Estimation of a Population Proportion
• Sample Size Considerations
• ### Chapter 8: Testing Hypotheses

• The Elements of Hypothesis Testing
• Large Sample Tests for a Population Mean
• The Observed Significance of a Test
• Small Sample Tests for a Population Mean
• Large Sample Tests for a Population Proportion
• ### Chapter 9: Two-Sample Problems

• Comparison of Two Population Means: Large, Independent Samples
• Comparison of Two Population Means: Small, Independent Samples
• Comparison of Two Population Means: Paired Samples
• Comparison of Two Population Proportions
• Sample Size Considerations
• ### Chapter 10: Correlation and Regression

• Linear Relationships Between Variables
• The Linear Correlation Coefficient
• Modelling Linear Relationships with Randomness Present
• The Least Squares Regression Line