# Applied Statistical Inference with MINITAB®, Second Edition

## Preview

## Book Description

Praise for the first edition:

*"One of my biggest complaints when I teach introductory statistics classes is that it takes me most of the semester to get to the good stuff—inferential statistics. The author manages to do this very quickly….if one were looking for a book that efficiently covers basic statistical methodology and also introduces statistical software [this text] fits the bill." *-**The American Statistician**

** Applied Statistical Inference with MINITAB, Second Edition distinguishes itself from other introductory statistics textbooks by **focusing on the applications of statistics without compromising mathematical rigor. It presents the material in a seamless step-by-step approach so that readers are first introduced to a topic, given the details of the underlying mathematical foundations along with a detailed description of how to interpret the findings, and are shown how to use the statistical software program Minitab to perform the same analysis.

- Gives readers a solid foundation in how to apply many different statistical methods.
- MINITAB is fully integrated throughout the text.
- Includes fully worked out examples so students can easily follow the calculations.
- Presents many new topics such as one- and two-sample variances, one- and two-sample Poisson rates, and more nonparametric statistics.
- Features mostly new exercises as well as the addition of
*Best Practices*sections that describe some common pitfalls and provide some practical advice on statistical inference.

This book is written to be user-friendly for students and practitioners who are not experts in statistics, but who want to gain a solid understanding of basic statistical inference. This book is oriented towards the practical use of statistics. The examples, discussions, and exercises are based on data and scenarios that are common to students in their everyday lives.

## Table of Contents

Chapter 1

Introduction

What is Statistics?

What This Book Is About

Summary Tables and Graphical Displays

Descriptive Representations of Data

Inferential Statistics

Populations

Different Ways to Collect Data

Types of Variables

Scales of Variables

Types of Analyses

Entering Data into Minitab

Best Practices

Chapter 2

Graphs and Charts

Introduction

Frequency Distributions and Histograms

Using Minitab to Create Histograms

Stem-and-Leaf Plots

Using Minitab to Create Stem-and-Leaf Plots

Bar Charts

Using Minitab to Create a Bar Chart

Boxplots

Using Minitab to Create Boxplots

Scatter Plots

Using Minitab to Create Scatter Plots

Marginal Plots

Using Minitab to Create Marginal Plots

Matrix Plots

Using Minitab to Create a Matrix Plot

Best Practices

Chapter 3

Descriptive Representations of Data and Random Variables

Introduction

Descriptive Statistics

Measures of Central Tendency

Measures of Variability

Using Minitab to Calculate Descriptive Statistics

More on Statistical Inference

Discrete Random Variables

Sampling Distributions

Continuous Random Variables

The Standard Normal Distribution

Non-Standard Normal Distributions

Other Discrete and Continuous Probability Distributions

The Binomial Distribution

The Poisson Distribution

The *t*-Distribution

The Chi-Square Distribution

The *F*-Distribution

Using MINTIAB to Graph Probability Distributions

Chapter 4

Statistical Inference for One Sample

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 Intervals and Hypothesis Tests for One Proportion

Using Minitab for a One-Sample Proportion

Power Analysis for a One-Sample Proportion

Confidence Intervals and Hypothesis Tests for One-Sample Variance

Confidence Intervals for One-Sample Variance

Hypothesis Tests for One-Sample Variance

Using Minitab for One-Sample Variance

Power Analysis for One-Sample Variance

Confidence Intervals for One-Sample Count Data

Using Minitab to Calculate Confidence Intervals for a One-Sample Count Variable

Hypothesis Test for a One-Sample Sample Count Variable

Using Minitab to Conduct a Hypothesis Test for a One-Sample Count Variable

Using Minitab for a Power Analysis for a One-Sample Poisson

A Note About One- and Two-Tailed Hypothesis Tests

Chapter 5

Statistical Inference for Two-Samples

Introduction

Confidence Interval for the Difference between Two Means

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

Hypothesis Tests for 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

Paired Confidence Interval and *t*-Test

Using Minitab for a Paired Confidence Interval and *t*-Test

Differences Between Two Proportions

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

Power Analysis for a Two-Sample Proportion

Confidence Intervals and Hypothesis Tests for Two Variances

Using Minitab for Testing Two Sample Variances

Power Analysis for a Two-Sample Variances

Confidence Intervals and Hypothesis Tests for Two Count Variables

Using Minitab for a Two-Sample Poisson

Power Analysis for a -Sample Poisson Rate

Best Practices

Chapter 6

Simple Linear Regression

Introduction

The Simple Linear Regression Model

Model Assumptions for Simple Linear Regression

Finding the Equation of the Line of Best Fit

Using Minitab for Simple Linear Regression

Standard Errors for Estimated Regression Parameters

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

Chapter 7

More on Simple Linear Regression

Introduction

The Coefficient of Determination

Using Minitab to Find the Coefficient of Determination

The 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: Standardized Residuals

Using Minitab to Calculate Standardized Residuals

Assessing Outliers: Cook’s Distances

Using Minitab to Find Cook’s Distances

How to Deal with Outliers

Chapter 8

Multiple Regression Analysis

Introduction

Basics of Multiple Regression Analysis

Using Minitab to Create Matrix Plots

Using Minitab for Multiple Regression

The Coefficient of Determination for Multiple Regression

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

Chapter 9

More on Multiple Regression

Introduction

Using Categorical Predictor Variables

Using Minitab for Categorical Predictor Variables

Adjusted

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

Chapter 10

Analysis of Variance (ANOVA)

Introduction

Basic Experimental Design

One-Way ANOVA

One-Way ANOVA Model Assumptions

Assumption of Constant Variance

Normality Assumption

Using Minitab for One-Way ANOVAs

Multiple Comparison Techniques

Using Minitab for Multiple Comparisons

Power Analysis and One-Way ANOVA

Chapter 11

Nonparametric Statistics

Introduction

Wilcoxon Signed-Rank Test

Using Minitab for the Wilcoxon Signed-Rank Test

The Mann-Whitney Test

Using Minitab for the Mann-Whitney Test

Kruskal–Wallis Test

Using Minitab for the Kruskal–Wallis Test

Chapter 12

Two Way Analysis of Variance and Basic Time Series

Two-Way Analysis of Variance

Using Minitab for a Two-Way ANOVA

Basic Time Series Analysis

## Author(s)

### Biography

**Sally A. Lesik** is a professor of mathematics at Central Connecticut State University. Dr. Lesik has taught many mathematics, statistics, engineering, and physics courses. Her primary research is in applied statistical inference.

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