Applied Statistical Inference with MINITAB®

Introduction

What This Book Is About

Types of Studies

What Is Statistics?

Types of Variables

Classification of Variables

Entering Data into MINITAB

Graphing Variables

Introduction

Histograms

Using MINITAB to Create Histograms

Stem-and-Leaf Plots

Using MINITAB to Create a Stem-and-Leaf Plot

Bar Charts

Using MINITAB to Create a Bar Chart

Box Plots

Using MINITAB to Create Box Plots

Scatter Plots

Using MINITAB to Create Scatter Plots

Marginal Plots

Using MINITAB to Create Marginal Plots

Descriptive Representations of Data and Random Variables

Introduction

Descriptive Statistics

Measures of Center

Measures of Spread

Using MINITAB to Calculate Descriptive Statistics

Random Variables and Their Distributions

Sampling Distributions

Basic Statistical Inference

Introduction

Confidence Intervals

Using MINITAB to Calculate Confidence Intervals for a Population Mean

Hypothesis Testing: A One-Sample t-Test for a Population Mean

Using MINITAB for a One-Sample t-Test

Power Analysis for a One-Sample t-Test

Using MINITAB for a Power Analysis for a One-Sample t-Test

Confidence Interval for the Difference between Two Means

Using MINITAB to Calculate a Confidence Interval for the Difference between Two Means

Testing the Difference between Two Means

Using MINITAB to Test the Difference between Two Means

Using MINITAB to Create an Interval Plot

Using MINITAB for a Power Analysis for a Two-Sample t-Test

Confidence Intervals and Hypothesis Tests for Proportions

Using MINITAB for a One-Sample Proportion

Power Analysis for a One-Sample Proportion

Differences between Two Proportions

Using MINITAB for Two-Sample Proportion Confidence Intervals and Hypothesis Tests

Power Analysis for a Two-Sample Proportion

Simple Linear Regression

Introduction

The Simple Linear Regression Model

Model Assumptions

Finding the Equation of the Line of Best Fit

Using MINITAB for Simple Linear Regression

Regression Inference

Inferences about the Population Regression Parameters

Using MINITAB to Test the Population Slope Parameter

Confidence Intervals for the Mean Response for a Specific Value of the Predictor Variable

Prediction Intervals for a Response for a Specific Value of the Predictor Variable

Using MINITAB to Find Confidence and Prediction Intervals

More on Simple Linear Regression

Introduction

The Coefficient of Determination

Using MINITAB to Find the Coefficient of Determination

The Sample Coefficient of Correlation

Correlation Inference

Using MINITAB for Correlation Analysis

Assessing Linear Regression Model Assumptions

Using MINITAB to Create Exploratory Plots of Residuals

A Formal Test of the Normality Assumption

Using MINITAB for the Ryan–Joiner Test

Assessing Outliers

Assessing Outliers: Leverage Values

Using MINITAB to Calculate Leverage Values

Assessing Outliers: Internally Studentized Residuals

Assessing Outliers: Cook’s Distances

Using MINITAB to Find Cook’s Distances

How to Deal with Outliers

Multiple Regression Analysis

Introduction

Basics of Multiple Regression Analysis

Using MINITAB to Create a Matrix Plot

Using MINITAB for Multiple Regression

The Coefficient of Determination for Multiple Regression

The Analysis of Variance Table

Testing Individual Population Regression Parameters

Using MINITAB to Test Individual Regression Parameters

Multicollinearity

Variance Inflation Factors

Using MINITAB to Calculate Variance Inflation Factors

Multiple Regression Model Assumptions

Using MINITAB to Check Multiple Regression Model Assumptions

Quadratic and Higher-Order Predictor Variables

Using MINITAB to Create a Quadratic Variable

More on Multiple Regression

Introduction

Using Categorical Predictor Variables

Using MINITAB for Categorical Predictor Variables

The Adjusted R²

Best Subsets Regression

Using MINITAB for Best Subsets Regression

Confidence and Prediction Intervals for Multiple Regression

Using MINITAB to Calculate Confidence and Prediction Intervals for a Multiple Regression Analysis

Assessing Outliers

Analysis of Variance (ANOVA)

Introduction

Basic Experimental Design

One-Way ANOVA

Model Assumptions

The Assumption of Constant Variance

The Normality Assumption

Using MINITAB for One-Way ANOVAs

Multiple Comparison Techniques

Using MINITAB for Multiple Comparisons

Power Analysis and One-Way ANOVA

Other Topics

Introduction

Two-Way Analysis of Variance

Using MINITAB for a Two-Way ANOVA

Nonparametric Statistics

Wilcoxon Signed-Rank Test

Using MINITAB for the Wilcoxon Signed-Rank Test

Kruskal–Wallis Test

Using MINITAB for the Kruskal–Wallis Test

Basic Time Series Analysis

Index

Exercises appear at the end of each chapter.