Applied Statistical Inference with MINITAB®

Sally A. Lesik is 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. .

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.