# Introduction to Statistical Methods and Regression Models

Lead Author(s): **Lelys Bravo de Guenni**

Student Price: **Contact us to learn more**

This book is an introduction to the main methods used in Statistical Inference and Regression Analysis, using real life examples and a statistical package outputs.

Content Index

# Introduction to Statistical Methods and Regression Models

Lelys Bravo de Guenni, PhD

# Table of Contents

## Chapter 1: Introduction to Statistical Thinking

- Questions to Chapter 1

## Chapter 2: Descriptive Statistics and Sampling Distributions

- Part I: Descriptive Statistics
- Part II: Sampling Distributions
- Question to Chapter 2

## Chapter 3: Basic Statistical Inference

- 3.1 Point Estimation
- 3.2 Interval Estimation
- 3.3 Hypothesis Testing
- Questions to Chapter 3

## Chapter 4: Correlation Analysis

- Part I: Definition of the Correlation Coefficient
- Part II: Hypothesis testing and confidence intervals for the correlation coefficient ρ
- Questions to Chapter 4

## Chapter 5: Simple Linear Regression Analysis

- Part I: Model assumptions and least-square estimation
- Part II: Inference on the linear regression equation
- Part III. The Analysis of Variance Table: Assessing the appropriateness of the straight-line regression
- Questions to Chapter 5

## Chapter 6: Multiple Regression Analysis

- Part I: Examples and Analysis of Variance for the Multiple Regression equation
- Part II: Statistical Inference in Multiple Regression
- Part III. Multiple correlation coefficient, partial correlation and multiple partial correlation coefficient
- Questions to Chapter 6

## Chapter 7: Dummy variables in regression and straight-line comparisons

- 7.1 Dummy Variables in Regression
- 7.2 Comparing two straight-lines
- Questions to Chapter 7

## Chapter 8: Regression Diagnostics and Best Model Selection

- Part I: Regression Diagnostics
- Part II: Selecting the Best Regression Equation
- Questions to Chapter 8