xxvii, 858 pages : 29 cm + Reducing the emphasis on doing computations, this practical text thoroughly integrates Microsoft Excel as a tool for analysis and presents statistical concepts in the context of the functional areas of business Includes bibliographical references and index Preface -- Chapter 1 -- Introduction and Data Collection -- 1.1 Why Learn Statistics -- 1.2 Statistics for Managers -- USING STATISTICS @ Good Tunes -- 1.3 Basic Vocabulary of Statistics -- 1.4 Data Collection -- 1.5 Types of Variables -- Levels of Measurement and Measurement Scales -- 1.6 Microsoft Excel Worksheets -- Worksheet Cells -- Designing Effective Worksheets -- Summary -- Key Terms -- Chapter Review Problems -- Introduction to the Web Cases -- Excel Companion to Chapter 1 -- E1.1 Preliminaries: Basic Computing Skills -- E1.2 Basic Workbook Operations -- E1.3 Worksheet Entries -- E1.4 Worksheet Formatting -- E1.5 Copy-and-Paste Operations -- E1.6 Add-ins: Making Things Easier for You -- Chapter 2 -- Presenting Data in Tables and Charts -- USING STATISTICS@ CHOICE IS YOURS -- 2.1 Tables and Charts for Categorical Data -- The Summary Table -- The Bar Chart -- The Pie Chart -- The Pareto Diagram -- 2.2 Organizing Numerical Data -- The Ordered Array -- The Stem-and-Leaf Display -- 2.3 Tables and Charts for Numerical Data -- The Frequency Distribution -- The Relative Frequency Distribution and the Percentage Distribution -- The Cumulative Distribution -- The Histogram -- The Polygon -- The Cumulative Percentage Polygon (Ogive) -- 2.4 Cross Tabulations -- The Contingency Table -- The Side-by-Side Bar Chart -- 2.5 Scatter Plots and Time-Series Plots -- The Scatter Plot -- The Time-Series Plot -- 2.6 Misusing Graphs and Ethical Issues -- Summary -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 2 -- E2.1 Creating Summary Tables -- E2.2 Creating Charts -- E2.3 Creating Bar and Pie Charts from Summary Tables -- E2.4 Creating Pareto Diagrams from Summary Tables -- E2.5 Creating an Ordered Array -- E2.6 Creating Stem-and Leaf Displays -- E2.7 Creating Frequency Distributions and Histograms -- E2.8 Creating a Histogram from Summarized Data -- E2.9 Creating Polygons -- E2.10 Creating Contingency Tables -- E2.11 Creating Side-by-Side Charts -- E2.12 Creating Scatter Plots -- E2.13 Creating Time Series Plots -- 3 Numerical Descriptive Measures -- Using Statistics@ Choice Is Yours -- 3.1 Measures of Central Tendency -- The Mean -- The Median -- The Mode -- Quartiles -- The Geometric Mean -- 3.2 Variation and Shape -- The Range -- The Interquartile Range -- The Variance and the Standard Deviation -- The Coefficient of Variation -- Z Scores -- Shape -- Visual Explorations: Exploring Descriptive Statistics -- Microsoft Excel Descriptive Statistics Output -- 3.3 Numerical Descriptive Measures for a Population -- The Population Mean -- The Population Variance and Standard Deviation -- The Empirical Rule -- The Chebychev Rule -- 3.4 Exploratory Data Analysis -- The Five-Number Summary -- The Box-and-Whisker Plot -- 3.5 The Covariance and the Coefficient of Correlation -- The Covariance -- The Coefficient of Correlation -- 3.6 Pitfalls in Numerical Descriptive Measures and Ethical Issues -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 3 -- E3.1 Computing Measures of Central Tendency, Variation, and Shape -- E3.2 Creating Dot Scale Diagrams -- E3.3 Computing Measures for a Population -- E3.4 Creating Box-and-Whisker Plots -- E3.5 Computing the Covariance -- E3.6 Computing the Correlation Coefficient -- 4 Basic Probability -- Using Statistics@The Consumer Electronics Company -- 4.1 Basic Probability Concepts -- Events and Sample Spaces -- Contingency Tables -- Simple (Marginal) Probability -- Joint Probability -- General Addition Rule -- 4.2 Conditional Probability -- Computing Conditional Probabilities -- Decision Trees -- Statistical Independence -- Multiplication Rules -- Marginal Probability Using the General Multiplication Rule -- 4.3 Bayes' Theorem -- 4.4 Ethical Issues and Probability -- CD-ROM Topic 4.5 Counting Rules -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Web Case -- Excel Companion to Chapter 4 -- E4.1 Computing Basic Probabilities -- E4.2 Using Bayes' Theorem -- 5 Some Important Discrete Probability Distributions -- Using Statistics@ Saxon Home Improvement -- 5.1 The Probability Distribution for a Discrete Random Variable -- Expected Value of a Discrete Random Variable -- Variance and Standard Deviation of a Discrete Random Variable -- 5.2 Covariance and Its Application in Finance -- The Covariance -- The Expected Value, Variance, and Standard Deviation of the Sum of Two -- Random Variables -- Portfolio Expected Return and Portfolio Risk -- 5.3 Binomial Distribution -- 5.4 Poisson Distribution -- 5.5 Hypergeometric Distribution -- 5.6 (CD ROM Topic) Using the Poisson Distribution to Approximate the Binomial -- Distribution -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 5 -- E5.1 Computing the Expected Value of a Discrete Random Variable -- E5.2 Computing Portfolio Expected Return & Portfolio Risk -- E5.3 Computing Binomial Probabilities -- E5.4 Computing Poisson Probabilities -- E5.5 Computing Hypergeometric Probabilities -- E5.6 Creating Histograms for Discrete Probability Distributions -- 6 The Normal Distribution and Other Continuous Distributions -- Using Statistics@OurCampus! -- 6.1 Continuous Probability Distributions -- 6.2 The Normal Distribution -- 6.3 Evaluating Normality -- Comparing Data Characteristics to Theoretical Properties -- Constructing the Normal Probability Plot -- 6.4 The Uniform Distribution -- 6.5 The Exponential Distribution -- CD-ROM Topic 6.6 The Normal Approximation to the Binomial Distribution -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 6 -- E6.1 Computing Normal Probabilities -- E6.2 Creating Normal Probability Plots -- E6.3 Computing Exponential Probabilities -- 7 Sampling and Sampling Distributions -- Using Statistics@Oxford Cereals -- 7.1 Types of Survey Sampling Methods -- Simple Random Sample -- Systematic Sample -- Stratified Sample -- Cluster Sample -- 7.2 Evaluating Survey Worthiness -- Survey Errors -- Ethical Issues -- 7.3 Sampling Distributions -- 7.4 Sampling Distribution of the Mean -- The Unbiased Property of the Sample Mean -- Standard Error of the Mean -- Sampling from Normally Distributed Populations -- Sampling from Nonnormally Distributed Populations-The Central Limit -- Theorem -- 7.5 Sampling Distribution of the Proportion -- 7.6 (CD-ROM Topic) Sampling from Finite Populations -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 7 -- E7.1 Creating Simple Random Samples (without replacement) -- E7.2 Creating Simulated Sampling Distributions -- 8 Confidence Interval Estimation -- Using Statistics@ SAXON HOME IMPROVEMENT -- 8.1 Confidence Interval Estimation for the Mean (? Known) -- 8.2 Confidence Interval Estimation for the Mean (? Unknown) -- Student's t Distribution -- Properties of the t Distribution -- The Concept of Degrees of Freedom -- The Confidence Interval Statement -- 8.3 Confidence Interval Estimation for the Proportion -- 8.4 Determining Sample Size -- Sample Size Determination for the Mean -- Sample Size Determination for the Proportion -- 8.5 Applications of Confidence Interval Estimation in Auditing -- Estimating the Population Total Amount -- Difference Estimation -- One-Sided Confidence Interval Estimation of the Rate of Noncompliance with Internal Controls -- 8.6 Confidence Interval Estimation and Ethical Issues -- 8.7 CD-ROM Topic: Estimation and Sample Size Determination for Finite -- Populations -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- EXCEL COMPANION to Chapter 8 -- E8.1 Computing the Confidence Interval Estimate for the Mean (? known) -- E8.2 Computing the Confidence Interval Estimate for the Mean (? unknown) -- E8.3 Computing the Confidence Interval Estimate for the Proportion -- E8.4 Computing the Sample Size Needed for Estimating the Mean -- E8.5 Computing the Sample Size Needed for Estimating the Proportion -- E8.6 Computing the Confidence Interval Estimate for the Population Total -- E8.7 Computing the Confidence Interval Estimate for the Total Difference -- E8.8 Computing Finite Population Correction Factors -- 9 Fundamentals of Hypothesis Testing: One-Sample Tests -- Using Statistics@ Oxford Cereals, Part II -- 9.1 Hypothesis-Testing Methodology -- The Null and Alternative Hypotheses -- The Critical Value of the Test Statistic -- Regions of Rejection and Nonrejection -- Risks in Decision Making Using Hypothesis-Testing Methodology -- 9.2 Z Test of Hypothesis for the Mean??? Known) -- The Critical Value Approach to Hypothesis Testing -- The p-Value Approach to Hypothesis Testing -- A Connection between Confidence Interval Estimation and Hypothesis -- Testing -- 9.3 One-Tail Tests -- The Critical Value Approach -- The p-Value Approach -- 9.4 t Test of Hypothesis for the Mean (? Unknown) -- The Critical Value Approach -- The p-Value Approach -- Checking Assumptions -- 9.5 Z Test of Hypothesis for the Proportion -- The Critical Value Approach -- The p-Value Approach -- 9.6 Potential Hypothesis-Testing Pitfalls and Ethical Issues -- 9.7 CD-ROM Topic The Power of a Test -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 9 E9.1 Using the Z Test for the Mean (? known) -- E9.2 Using the t Test for the Mean (? unknown) -- E9.3 Using the Z Test for the Proportion -- 10 Two-Sample Tests -- Using Statistics@BLK Foods -- 10.1 Comparing the Means of Two Independent Populations -- Z Test for the Difference Between Two Means -- Pooled-Variance t Test for the Difference Between Two Means -- Confidence Interval Estimate for the Difference Between Two Means -- Separate-Variance t Test for the Difference Between Two Means -- 10.2 Comparing the Means of Two Related Populations -- Paired t Test -- Confidence Interval Estimate for the Mean Difference -- 10.3 Comparing Two Population Proportions -- Z Test for the Difference Between Two Proportions -- Confidence Interval Estimate for the Difference Between Two Proportions -- 10.4 F Test for the Difference Between Two Variances -- Finding Lower-Tail Critical Values -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 10 -- Two-Sample Hypothesis Testing in Microsoft Excel -- E10.1 Using the Z Test for the Difference Between Two Means (Unsummarized Data) -- E10.2 Using the Z Test for the Difference Between Two Means (Summarized Data) -- E10.3 Using the Pooled-Variance t Test (Unsummarized Data) -- E10.4 Using the Pooled-Variance t Test (Summarized Data) -- E10.5 Using the Separate-Variance t Test for the Difference Between Two Means (Unsummarized Data) -- E10.6 Using the Paired t Test for the Difference Between Two Means (Unsummarized Data) -- E10.7 Using the Z Test for the Difference Between Two Proportions (Summarized Data) -- E10.8 Using the F Test for the Difference Between Two Variances (Unsummarized Data) -- E10.9 Using the F Test for the Difference Between Two Variances (Summarized Data) -- 11 Analysis of Variance -- Using Statistics @ Perfect Parachutes -- 11.1 The Completely Randomized Design: One-Way Analysis of Variance -- F Test for Differences Among More Than Two Means -- Multiple Comparisons: The Tukey-Kramer Procedure -- ANOVA Assumptions -- Levene's Test for Homogeneity of Variance -- 11.2 The Factorial Design: Two-Way Analysis of Variance -- Testing for Factor and Interaction Effects -- Interpreting Interaction Effects -- Multiple Comparisons: The Tukey Procedure -- 11.3 CD-ROM Topic The Randomized Block Design -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 11 -- E11.1 Using the F Test for Differences Among More Than Two Means -- E11.2 Using the Tukey-Kramer Procedure -- E11.3 Using the Levene Test for Homogeneity of Variance -- E11.4 Using The Two-Way ANOVA -- 12 Chi-Square Tests and Nonparametric Tests -- Using Statistics@ T.C. Resort Properties -- 12.1 Chi-Square Test for the Difference Between Two Proportions (Independent Samples) -- 12.2 Chi-Square Test for Differences Among More than Two Proportions -- The Marascuilo Procedure -- 12.3 Chi-Square Test of Independence -- 12.4 McNemar Test for the Difference Between Two Proportions (Related Samples) -- 12.5 Wilcoxon Rank Sum Test: Nonparametric Analysis for Two Independent Populations -- 12.6 Kruskal-Wallis Rank Test: Nonparametric Analysis for the One-Way ANOVA -- 12.7 CD-ROM Topic Chi-Square Test for a Variance or Standard Deviation -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 12 -- E12.1 Using the Chi-Square Test for the Difference Between Two Proportions -- E12.2 Using the Chi-Square Test for the Differences in More Than Two Proportions -- E12.3 Using the Chi-Square Test of Independence -- E12.4 Using the McNemar Test -- E12.5 Using the Wilcoxon Rank Sum Test -- E12.6 Using the Kruskal-Wallis Rank Test -- 13 Simple Linear Regression -- Using Statistics@ Sunflowers Apparel -- 13.1 Types of Regression Models -- 13.2 Determining the Simple Linear Regression Equation -- The Least-Squares Method -- Visual Explorations: Exploring Simple Linear Regression Coefficients -- Predictions in Regression Analysis: Interpolation versus Extrapolation -- Computing the Y Intercept b0 and the Slope b1 -- 13.3 Measures of Variation -- Computing the Sum of Squares -- The Coefficient of Determination -- Standard Error of the Estimate -- 13.4 Assumptions -- 13.5 Residual Analysis -- Evaluating the Assumptions -- 13.6 Measuring Autocorrelation: The Durbin-Watson Statistic -- Residual Plots to Detect Autocorrelation -- The Durbin-Watson Statistic -- 13.7 Inferences About the Slope and Correlation Coefficient -- t Test for the Slope -- F Test for the Slope -- Confidence Interval Estimate for the Slope (?1) -- t Test for the Correlation Coefficient -- 13.8 Estimation of Mean Values and Prediction of Individual Values -- The Confidence Interval Estimate -- The Prediction Interval -- 13.9 Pitfalls in Regression and Ethical Issues -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 13 -- E13.1 Performing Simple Linear Regression Analysis -- E13.2 Creating Scatter Diagrams and Adding a Prediction Line -- E13.3 Performing Residual Analyses -- E13.4 Computing the Durbin-Watson Statistic -- E13.5 Estimating the Mean of Y and Predicting Y Values -- E13.6 Example: Sunflowers Site Selection Data -- 14 Introduction to Multiple Regression -- Using Statistics@ OMNIFOODS -- 14.1 Developing the Multiple Regression Model -- Interpreting the Regression Coefficients -- Predicting the Dependent Variable Y -- 14.2 R2, Adjusted R2, and the Overall F Test -- Coefficient of Multiple Determination -- Test for the Significance of the Overall Multiple Regression Model -- 14.3 Residual Analysis for the Multiple Regression Model -- 14.4 Inferences Concerning the Population Regression Coefficients -- Tests of Hypothesis -- Confidence Interval Estimation -- 14.5 Testing Portions of the Multiple Regression Model -- Coefficients of Partial Determination -- 14.6 Using Dummy Variables and Interaction Terms in Regression Models -- Interactions -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 14 -- E14.1 Creating Multiple Regression Models -- E14.2 Creating Multiple Regression Residual Plots -- E14.3 Computing the Confidence Interval Estimate of the Mean and Prediction -- Interval -- E14.4 Computing the Coefficients of Partial Determination -- E14.5 Creating Dummy Variables -- E14.6 Creating Interaction Terms 15 Multiple Regression Model Building -- USING STATISTICS@WTT-TV -- 15.1 The Quadratic Regression Model -- Finding the Regression Coefficients and Predicting Y -- Testing for the Significance of the Quadratic Model -- Testing the Quadratic Effect -- The Coefficient of Multiple Determination -- 15.2 Using Transformations in Regression Models -- The Square-Root Transformation -- The Log Transformation -- 15.3 Collinearity -- 15.4 Model Building -- The Stepwise Regression Approach to Model Building -- The Best-Subsets Approach to Model Building -- Model Validation -- 15.5 Pitfalls in Multiple Regression and Ethical Issues -- Pitfalls in Multiple Regression -- Ethical Issues -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- The Mountain States Potato Company Case -- Web Case -- Excel Companion to Chapter 15 -- E15.1 Creating a Quadratic Term -- E15.2 Creating Transformations -- E15.3 Computing Variance Inflationary Factors -- E15.4 Using Stepwise Regression -- E15.5 Using Best-Subsets Regression -- 16 Time-Series Forecasting and Index Numbers -- Using Statistics@ THE PRINCIPLED -- 16.1 The Importance of Business Forecasting -- 16.2 Component Factors of the Classical Multiplicative Time-Series Model -- 16.3 Smoothing the Annual Time Series -- Moving Averages -- Exponential Smoothing -- 16.4 Least-Squares Trend-Fitting and Forecasting -- The Linear Trend Model -- The Quadratic Trend Model -- The Exponential Trend Model -- Model Selection Using First, Second, and Percentage Differences -- 16.5 Autoregressive Modeling for Trend-Fitting and Forecasting -- 16.6 Choosing an Appropriate Forecasting Model -- Performing a Residual Analysis -- Measuring the Magnitude of the Residual Error through Squared or -- Absolute Differences -- Principle of Parsimony -- A Comparison of Four Forecasting Methods -- 16.7 Time-Series Forecasting of Seasonal Data -- Least-Squares Forecasting with Monthly or Quarterly Data -- 16.8 Index Numbers -- The Price Index -- Aggregate Price Indexes -- Weighted Aggregate Price Indexes -- Some Common Price Indexes -- 16.9 Pitfalls Concerning Time-Series Forecasting -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Managing the Springville Herald -- Web Case -- Excel Companion to Chapter 16 -- E16.1 Computing Moving Averages -- E16.2 Creating Time-Series Plots -- E16.3 Creating Exponentially Smoothed Values -- E16.4 Creating Coded X Variables -- E16.5 Creating Quadratic and Exponential Terms -- E16.6 Using Least-Squares Linear Trend Fitting -- E16.7 Using Least-Squares Quadratic Trend Fitting -- E16.8 Using Least-Squares Exponential Trend Fitting -- E16.9 Creating Lagged Independent Variables -- E16.10 Creating First-Order Autoregressive Models -- E16.11 For Second-Order or Third-Order Autoregressive Models -- E16.12 Computing the Mean Absolute Deviation (MAD) -- E16.13 Creating Dummy Variables for Quarterly or Monthly Data -- E16.14 Calculating Index Numbers -- 17 Decision Making -- Using Statistics@Reliable Fund -- 17.1 Payoff Tables and Decision Trees -- 17.2 Criteria for Decision Making -- Expected Monetary Value -- Expected Opportunity Loss -- Return-to-Risk Ratio -- 17.3 Decision Making with Sample Information -- 17.4 Utility -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- Web Case -- Excel Companion to Chapter 17 -- E17.1 Computing Opportunity Loss -- E17.2 Computing Expected Monetary Value -- 18 Statistical Applications in Quality and Productivity Management -- Using Statistics@ BEACHCOMBER HOTEL -- 18.1 Total Quality Management -- 18.2 Six Sigma Management -- 18.3 The Theory of Control Charts -- 18.4 Control Chart for the Proportion-The p Chart -- 18.5 The Red Bead Experiment: Understanding Process Variability -- 18.6 Control Charts for the Range and the Mean -- The R Chart -- The Chart -- 18.7 Process Capability -- Customer Satisfaction and Specification Limits -- Capability Indexes -- CPL, CPU, and Cpk -- Summary -- Key Equations -- Key Terms -- Chapter Review Problems -- The Harnswell Sewing Machine Company Case -- Managing the Springville Herald -- Excel Companion to Chapter 18 -- E18.1 Creating p Charts -- E18.2 Creating R and Charts -- Appendices -- A. Review of Arithmetic, Algebra, and Logarithms -- B. Summation Notation -- C. Statistical Symbols and Greek Alphabet -- D. CD-ROM Contents -- E. Tables -- F. Configuring Microsoft Excel and Installing PHStat -- Self-Test Solutions and Answers to Selected Even-Numbered Problems -- Index -- CD-ROM Topics (available as Adobe Reader .PDF files on the text CD) -- 4.5 Counting Rules -- 5.6 Using the Poisson Distribution to Approximate the Binomial Distribution -- 6.6 The Normal Approximation to the Binomial Distribution -- 7.6 Sampling from Finite Populations -- 8.7 Estimation and Sample Size Determination for Finite Populations -- 9.7 The Power of a Test -- 11.3 The Randomized Block Design -- 12.7 Chi-Square Test for a Variance or Standard Deviation System requirements for accompanying disc: 200 MHz Pentium II Processor; 64 MB RAM; 57.1 MB free hard disk space; Windows ME/2000/NT/XP/Vista; Microsoft Excel