ISBN-10:
1420065831
ISBN-13:
2901420065830
Pub. Date:
12/22/2009
Publisher:
Taylor & Francis
Applied Statistical Inference with MINITAB / Edition 1

Applied Statistical Inference with MINITAB / Edition 1

by Sally Lesik
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  • Product Details

    ISBN-13: 2901420065830
    Publisher: Taylor & Francis
    Publication date: 12/22/2009
    Series: Statistics: A Series of Textbooks and Monographs Series
    Edition description: New Edition
    Pages: 464
    Product dimensions: 6.50(w) x 1.50(h) x 9.50(d)

    About the Author

    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.

    .

    Table of Contents

    Preface xiii

    Acknowledgments xvii

    1 Introduction 1

    1.1 What This Book Is About 1

    1.1.1 Graphical Displays of Data 2

    1.1.2 Descriptive Representations of Data 2

    1.1.3 Basic Statistical Inference 3

    1.1.4 Regression Analysis 3

    1.1.5 Analysis of Variance 3

    1.2 Types of Studies 4

    1.3 What Is Statistics? 5

    1.4 Types of Variables 6

    1.5 Classification of Variables 7

    1.6 Entering Data into MINITAB® 9

    Exercises 12

    2 Graphing Variables 15

    2.1 Introduction 15

    2.2 Histograms 15

    2.3 Using MINITAB to Create Histograms 17

    2.4 Stem-and-Leaf Plots 18

    2.5 Using MINITAB to Create a Stem-and-Leaf Plot 23

    2.6 Bar Charts 24

    2.7 Using MINITAB to Create a Bar Chart 24

    2.8 Box Plots 25

    2.9 Using MINITAB to Create Box Plots 30

    2.10 Scatter Plots 31

    2.11 Using MINITAB to Create Scatter Plots 35

    2.12 Marginal Plots 39

    2.13 Using MINITAB to Create Marginal Plots 39

    Exercises 39

    3 Descriptive Representations of Data and Random Variables 49

    3.1 Introduction 49

    3.2 Descriptive Statistics 49

    3.3 Measures of Center 50

    3.4 Measures of Spread 54

    3.5 Using MINITAB to Calculate Descriptive Statistics 58

    3.6 Random Variables and Their Distributions 61

    3.7 Sampling Distributions 63

    Exercises 74

    4 Basic Statistical Inference 83

    4.1 Introduction 83

    4.2 Confidence Intervals 83

    4.3 Using MINITAB to Calculate Confidence Intervals for a Population Mean 89

    4.4 Hypothesis Testing: A One-Sample t-Test for a Population Mean 91

    4.5 Using MINITAB for a One-Sample t-Test 97

    4.6 Power Analysis for a One-Sample t-Test 103

    4.7 Using MINITAB for a Power Analysis for a One-Sample t-Test 104

    4.8 Confidence Interval for the Difference betweenTwo Means 110

    4.9 Using MINITAB to Calculate a Confidence Interval for the Difference between Two Means 112

    4.10 Testing the Difference between Two Means 115

    4.11 Using MINITAB to Test the Difference between Two Means 118

    4.12 Using MINITAB to Create an Interval Plot 119

    4.13 Using MINITAB for a Power Analysis for a Two-Sample t-Test 121

    4.14 Confidence Intervals and Hypothesis Tests for Proportions 127

    4.15 Using MINITAB for a One-Sample Proportion 131

    4.16 Power Analysis for a One-Sample Proportion 133

    4.17 Differences between Two Proportions 135

    4.18 Using MINITAB for Two-Sample Proportion Confidence Intervals and Hypothesis Tests 139

    4.19 Power Analysis for a Two-Sample Proportion 141

    Exercises 144

    Reference 154

    5 Simple Linear Regression 155

    5.1 Introduction 155

    5.2 Simple Linear Regression Model 156

    5.3 Model Assumptions 163

    5.4 Finding the Equation of the Line of Best Fit 164

    5.5 Using MINITAB for Simple Linear Regression 167

    5.6 Regression Inference 171

    5.7 Inferences about the Population Regression Parameters 172

    5.8 Using MINITAB to Test the Population Slope Parameter 175

    5.9 Confidence Intervals for the Mean Response for a Specific Value of the Predictor Variable 177

    5.10 Prediction Intervals for a Response for a Specific Value of the Predictor Variable 178

    5.11 Using MINITAB to Find Confidence and Prediction Intervals 180

    Exercises 190

    6 More on Simple Linear Regression

    6.1 Introduction 193

    6.2 Coefficient of Determination 193

    6.3 Using MINITAB to Find the Coefficient of Determination 195

    6.4 Sample Coefficient of Correlation 196

    6.5 Correlation Inference 200

    6.6 Using MINITAB for Correlation Analysis 204

    6.7 Assessing Linear Regression Model Assumptions 204

    6.8 Using MINITAB to Create Exploratory Plots of Residuals 206

    6.9 Formal Test of the Normality Assumption 217

    6.10 Using MINITAB for the Ryan-Joiner Test 219

    6.11 Assessing Outliers 219

    6.12 Assessing Outliers: Leverage Values 221

    6.13 Using MINITAB to Calculate Leverage Values 222

    6.14 Assessing Outliers: Internally Studentized Residuals 225

    6.15 Using MINITAB to Calculate Internally Studentized Residuals 226

    6.16 Assessing Outliers: Cook's Distances 228

    6.17 Using MINITAB to Find Cook's Distances 228

    6.18 How to Deal with Outliers 229

    Exercises 231

    References 238

    7 Multiple Regression Analysis 239

    7.1 Introduction 239

    7.2 Basics of Multiple Regression Analysis 239

    7.3 Using MINITAB to Create a Matrix Plot 242

    7.4 Using MINITAB for Multiple Regression 245

    7.5 Coefficient of Determination for Multiple Regression 248

    7.6 Analysis of Variance Table 248

    7.7 Testing Individual Population Regression Parameters 253

    7.8 Using MINITAB to Test Individual Regression Parameters 256

    7.9 Multicollinearity 257

    7.10 Variance Inflation Factors 258

    7.11 Using MINITAB to Calculate Variance Inflation Factors 261

    7.12 Multiple Regression Model Assumptions 264

    7.13 Using MINITAB to Check Multiple Regression Model Assumptions 264

    7.14 Quadratic and Higher-Order Predictor Variables 268

    7.15 Using MINITAB to Create a Quadratic Variable 268

    Exercises 273

    8 More on Multiple Regression 277

    8.1 Introduction 277

    8.2 Using Categorical Predictor Variables 277

    8.3 Using MINITAB for Categorical Predictor Variables 279

    8.4 Adjusted R2 284

    8.5 Best Subsets Regression 289

    8.6 Using MINITAB for Best Subsets Regression 296

    8.7 Confidence and Prediction Intervals for Multiple Regression 298

    8.8 Using MINITAB to Calculate Confidence and Prediction Intervals for a Multiple Regression Analysis 299

    8.9 Assessing Outliers 302

    Exercises 303

    9 Analysis of Variance (ANOVA) 307

    9.1 Introduction 307

    9.2 Basic Experimental Design 307

    9.3 One-Way ANOVA 309

    9.4 Model Assumptions 316

    9.5 Assumption of Constant Variance 317

    9.6 Normality Assumption 322

    9.7 Using MINITAB for One-Way ANOVAs 323

    9.8 Multiple Comparison Techniques 338

    9.9 Using MINTTAB for Multiple Comparisons 343

    9.10 Power Analysis and One-Way ANOVA 344

    Exercises 348

    References 351

    10 Other Topics 353

    10.1 Introduction 353

    10.2 Two-Way Analysis of Variance 353

    10.3 Using MINITAB for a Two-Way ANOVA 360

    10.4 Nonparametric Statistics 377

    10.5 Wilcoxon Signed-Rank Test 378

    10.6 Using MINITAB for the Wilcoxon Signed-Rank Test 382

    10.7 Kruskal-Wallis Test 388

    10.8 Using MINITAB for the Kruskal-Wallis Test 391

    10.8 Basic Time Series Analysis 398

    Exercises 411

    Appendix A 415

    Index 427

    What People are Saying About This

    From the Publisher

    … I was pleased to see this recently published textbook by Sally A. Lesik. Although its focus is on applications, formulas are not forgotten. The ample problem section at the end of the chapter requires the student to hand calculate values, but then verify the answers with the software. In fact, the book comes with a disc of MS Excel data worksheets. … a good choice for general students … This book is also a great choice for someone who wishes to teach themselves Minitab.
    Significance, May 2011

    The book is a great reference for anyone who is new to Minitab or is an infrequent user who just wants a quick reference. It is well organized by topic… . Applied Statistical Inference with MINITAB (ASIM) could also be used as a text for students who have already had an introductory statistics class; I envision it for use by students in a research methods type of course. … 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. … (I will be taking some lessons on how to speed through the material.) … it is excellent as a quick review for those students who have already had some previous exposure. … Every set of clearly written Minitab instructions includes appropriate screen shots, all of which should be accessible to those having little software experience.… All in all, I recommend ASIM. … if one were looking for a book that efficiently covers basic statistical methodology and also introduces statistical software, ASIM fits the bill. …
    The American Statistician, February 2011, Vol. 65, No. 1

    This book/CD-ROM package is intended for a first course on applied inference for undergraduates and graduates in any field that uses statistics. The text is written to be beginner-friendly and oriented toward practical use of statistics, with less emphasis on theory.
    Book News, June 2010

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