Table Of Contents:
Preface xiii

Statistics, Data, and Statistical Thinking 2(36)

The Science of Statistics 4(1)

Types of Statistical Applications in Business 5(2)

Fundamental Elements of Statistics 7(5)

Processes (Optional) 12(3)

Types of Data 15(2)

Collecting Data 17(3)

The Role of Statistics in Managerial Decision Making 20(18)

Statistics in Action A 20/20 View of Surveys: Fact or Fiction? 3(25)

Using Technology Accessing and Listing Data in SPSS, MINITAB, and Excel 28(10)

Methods for Describing Sets of Data 38(92)

Describing Qualitative Data 40(9)

Graphical Methods for Describing Quantitative Data 49(13)

Summation Notation 62(1)

Numerical Measures of Central Tendency 63(11)

Numerical Measures of Variability 74(6)

Interpreting the Standard Deviation 80(7)

Numerical Measures of Relative Standing 87(4)

Methods for Detecting Outliers (Optional) 91(9)

Graphing Bivariate Relationships (Optional) 100(5)

The Time Series Plot (Optional) 105(3)

Distorting the Truth with Descriptive Techniques 108(22)

Statistics in Action Factors That Influence a Doctor to Refuse Ethics Consultation 39(82)

Using Technology Describing Data Using SPSS, MINITAB, and Excel/PHStat2 121(7)

Real-World Case The Kentucky Milk Case---Part I (A Case Covering Chapters 1 and 2) 128(2)

Probability 130(58)

Events, Sample Spaces, and Probability 132(14)

Unions and Intersections 146(2)

Complementary Events 148(1)

The Additive Rule and Mutually Exclusive Events 149(6)

Conditional Probability 155(4)

The Multiplicative Rule and Independent Events 159(11)

Random Sampling 170(3)

Bayes's Rule (Optional) 173(15)

Statistics in Action Lotto Buster! 131(53)

Using Technology Generating a Random Sample Using SPSS, MINITAB, and Excel/PHStat2 184(4)

Random Variables and Probability Distributions 188(102)

Two Types of Random Variables 190(3)

Probability Distributions for Discrete Random Variables 193(11)

The Binomial Distribution 204(14)

The Poisson Distribution (Optional) 218(5)

Probability Distributions for Continuous Random Variables 223(1)

The Uniform Distribution (Optional) 224(4)

The Normal Distribution 228(15)

Descriptive Methods for Assessing Normality 243(7)

Approximating a Binomial Distribution with a Normal Distribution (Optional) 250(6)

Sampling Distributions 256(6)

The Sampling Distribution of x and the Central Limit Theorem 262(28)

Statistics in Action Super Weapons Development---Optimizing the Hit Ratio 189(90)

Using Technology Binomial Probabilities, Normal Probabilities, and Simulated Sampling Distributions Using SPSS, MINITAB, and Excel/PHStat2 279(10)

Real-World Case The Furniture Fire Case (A Case Covering Chapters 3-4) 289(1)

Inferences Based on a Single Sample: Estimation with Confidence Intervals 290(54)

Identifying the Target Parameter 291(1)

Large-Sample Confidence Interval for a Population Mean 292(9)

Small-Sample Confidence Interval for a Population Mean 301(12)

Large-Sample Confidence Interval for a Population Proportion 313(7)

Determining the Sample Size 320(7)

Finite Population Correction for Simple Random Sampling (Optional) 327(3)

Sample Survey Designs (Optional) 330(14)

Statistics in Action Scallops, Sampling, and the Law 291(48)

Using Technology Confidence Intervals Using SPSS, MINITAB, and Excel/PHStat2 339(5)

Inferences Based on a Single Sample: Tests of Hypothesis 344(58)

The Elements of a Test of Hypothesis 345(7)

Large-Sample Test of Hypothesis about a Population Mean 352(8)

Observed Significance Levels: p-Values 360(7)

Small-Sample Test of Hypothesis about a Population Mean 367(6)

Large-Sample Test of Hypothesis about a Population Proportion 373(6)

Calculating Type II Error Probabilities: More about β (Optional) 379(8)

Test of Hypothesis about a Population Variance (Optional) 387(15)

Statistics, in Action Diary of a Kleenex® User 345(53)

Using Technology Tests of Hypotheses Using SPSS, MINITAB, and Excel/PHStat2 398(4)

Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses 402(72)

Identifying the Target Parameter 404(1)

Comparing Two Population Means: Independent Sampling 404(19)

Comparing Two Population Means: Paired Difference Experiments 423(13)

Comparing Two Population Proportions: Independent Sampling 436(9)

Determining the Sample Size 445(4)

Comparing Two Population Variances: Independent Sampling (Optional) 449(25)

Statistics in Action The Effect of Self-Managed Work Teams on Family Life 403(70)

Using Technology Two Sample Inferences Using SPSS, MINITAB, and Excel/PHStat2 466(7)

Real-World Case The Kentucky Milk Case---Part II (A Case Covering Chapters 5-7) 473(1)

Design of Experiments and Analysis of Variance 474(78)

Elements of a Designed Experiment 476(6)

The Completely Randomized Design: Single Factor 482(18)

Multiple Comparisons of Means 500(7)

The Randomized Block Design 507(14)

Factorial Experiments 521(31)

Statistics in Action The Ethics of Downsizing 475(71)

Using Technology Analysis of Variance Using SPSS, MINITAB, and Excel/PHStat2 546(6)

Categorical Data Analysis 552(44)

Categorical Data and the Multinomial Experiment 553(2)

Testing Category Probabilities: One-Way Table 555(9)

Testing Category Probabilities: Two-Way (Contingency) Table 564(16)

A Word of Caution about Chi-Square Tests 580(16)

Statistics in Action A Study of Coupon Users---Mail versus the Internet 553(35)

Using Technology Chi-Square Analyses Using SPSS, MINITAB, and Excel/PHStat2 588(6)

Real-World Case Discrimination in the Workplace (A Case Covering Chapters 8-9) 594(2)

Pimple Linear Regression 596(68)

Probabilistic Models 598(3)

Fitting the Model: The Least Squares Approach 601(14)

Model Assumptions 615(1)

An Estimator of σ2 616(4)

Assessing the Utility of the Model: Making Inferences about the Slope β1 620(8)

The Coefficient of Correlation 628(4)

The Coefficient of Determination 632(7)

Using the Model for Estimation and Prediction 639(8)

A Complete Example 647(17)

Statistics in Action An MBA's Work-Life Balance 597(62)

Using Technology Simple Linear Regression Using SPSS, MINITAB, and Excel/PHStat2 659(5)

Multiple Regression and Model Building 664(124)

Multiple Regression Models 665(2)

The First-Order Model: Estimating and Interpreting the β-Parameters 667(6)

Inferences about the β-Parameters and the Overall Model Utility 673(14)

Using the Model for Estimation and Prediction 687(7)

Model Building: Interaction Models 694(7)

Model Building: Quadratic and Other Higher-Order Models 701(10)

Model Building: Qualitative (Dummy) Variable Models 711(7)

Model Building: Models with Both Quantitative and Qualitative Variables (Optional) 718(9)

Model Building: Comparing Nested Models (Optional) 727(9)

Model Building: Stepwise Regression (Optional) 736(8)

Residual Analysis: Checking the Regression Assumptions 744(17)

Some Pitfalls: Estimability, Multicollinearity, and Extrapolation 761(27)

Statistics in Action Bid-Rigging in the Highway Construction Industry 665(117)

Using Technology Multiple Regression Using SPSS, MINITAB, and Excel/PHStat2 782(4)

Real-World Case The Condo Sales Case (A Case Covering Chapters 10-11) 786(2)

Methods for Quality Improvement 788(2)

Quality, Processes, and Systems 790(5)

Statistical Control 795(9)

The Logic of Control Charts 804(4)

A Control Chart for Monitoring the Mean of a Process: The x-Chart 808(16)

A Control Chart for Monitoring the Variation of a Process: The R-Chart 824(10)

A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The p-Chart 834(9)

Diagnosing the Causes of Variation (Optional) 843(2)

Capability Analysis (Optional) 845

Statistics in Action Testing Jet Fuel Additive for Safety 789(70)

Using Technology Control Charts Using SPSS, MINITAB, and Excel/PHStat2 859(5)

Real-World Case The Gasket Manufacturing Case (A Case Covering Chapter 12) 864

Time Series: Descriptive Analyses, Models, and Forecasting (Available on CD) 13-2(1)

Descriptive Analysis: Index Numbers 13-4(1)

Descriptive Analysis: Exponential Smoothing 13-14(1)

Time Series Components 13-20(1)

Forecasting: Exponential Smoothing 13-21(1)

Forecasting Trends: The Holt-Winters Forecasting Model (Optional) 13-24(1)

Measuring Forecast Accuracy: MAD and RMSE 13-29(1)

Forecasting Trends: Simple Linear Regression 13-34(1)

Seasonal Regression Models 13-38(1)

Autocorrelation and the Durbin-Watson Test 13-44(1)

Statistics in Action Forecasting the Monthly Sales of a New Cold Medicine 13-3(1)

Using Technology Forecasting Using SPSS, MINITAB, and Excel 13-59(1)

Real-World Case The Gasket Manufacturing Case (A Case Covering Chapters 12-13) 13-60(1)

Nonparametric Statistics (Available on CD) 14-2(1)

Introduction: Distribution-Free Tests 14-4(1)

Single Population Inferences 14-5(1)

Comparing Two Populations: Independent Samples 14-11(1)

Comparing Two Populations: Paired Difference Experiment 14-19(1)

Comparing Three or More Populations: Completely Randomized Design 14-27(1)

Comparing Three or More Populations: Randomized Block Design (Optional) 14-33(1)

Rank Correlation 14-38(868)

Statistics in Action Deadly Exposure: Agent Orange and Vietnam Vets 14-3(1)

Using Technology Nonparametric Tests Using SPSS, MINITAB, and Excel and PHStat2 14-53(868)

APPENDICES

Appendix A Basic Counting Rules 868(3)

Appendix B Tables 871(31)

Table I Random Numbers 872(3)

Table II Binomial Probabilities 875(4)

Table III Poisson Probabilities 879(5)

Table IV Normal Curve Areas 884(1)

Table V Critical Values of t 885(1)

Table VI Critical Values of χ2 886(2)

Table VII Percentage Points of the F-Distribution, α = .10 888(2)

Table VIII Percentage Points of the F-Distribution, α = .05 890(2)

Table IX Percentage Points of the F-Distribution, α = .025 892(2)

Table X Percentage Points of the F-Distribution, α = .01 894(2)

Table XI Control Chart Constants 896(1)

Table XII Critical Values for the Durbin-Watson d Statistic, α = .05 897(1)

Table XIII Critical Values for the Durbin-Watson d Statistic, α = .01 898(1)

Table XIV Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples 899(1)

Table XV Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test 900(1)

Table XVI Critical Values of Spearman's Rank Correlation Coefficient 901(1)

Appendix C Calculation Formulas for Analysis of Variance 902
Answers to Selected Exercises 1(1)
Index 1(1)
Photo Credits 1