{"product_id":"business-statistics-9781119668015","title":"Business Statistics","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eBusiness Statistics\u003c\/i\u003econtinues the tradition of presenting and explaining the wonders of business statistics through a clear, complete, student-friendly pedagogy. \u003cbr\u003e\u003cbr\u003eIn this 10thedition, author Ken Black uses current real-world data to equip students with thebusiness analytics techniquesandquantitative decision-making skillsrequired to make smart decisions in today's workplace.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface vii\u003c\/p\u003e \u003cp\u003eAbout the Author xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 \u003c\/b\u003e\u003cb\u003eIntroduction to Statistics and Business Analytics 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Statistics Describe the State of Business in India’s Countryside 1\u003c\/p\u003e \u003cp\u003e1.1 Basic Statistical Concepts 3\u003c\/p\u003e \u003cp\u003e1.2 Data Measurement 6\u003c\/p\u003e \u003cp\u003e1.3 Introduction to Business Analytics 9\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 15\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 15\u003c\/p\u003e \u003cp\u003eEthical Considerations 15\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Digiorno Pizza: Introducing a Frozen Pizza to Compete with Carry-Out 20\u003c\/p\u003e \u003cp\u003eBig Data Case 20\u003c\/p\u003e \u003cp\u003eReferences 21\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Visualizing Data with Charts and Graphs 22\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Container Shipping Companies 22\u003c\/p\u003e \u003cp\u003e2.1 Frequency Distributions 24\u003c\/p\u003e \u003cp\u003e2.2 Quantitative Data Graphs 27\u003c\/p\u003e \u003cp\u003e2.3 Qualitative Data Graphs 34\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 38\u003c\/p\u003e \u003cp\u003e2.4 Charts and Graphs for Two Variables 41\u003c\/p\u003e \u003cp\u003e2.5 Visualizing Time-Series Data 44\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 47\u003c\/p\u003e \u003cp\u003eEthical Considerations 48\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Southwest Airlines 54\u003c\/p\u003e \u003cp\u003eBig Data Case 55\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Descriptive Statistics 56\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Laundry Statistics 56\u003c\/p\u003e \u003cp\u003e3.1 Measures of Central Tendency 57\u003c\/p\u003e \u003cp\u003e3.2 Measures of Variability 65\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 67\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 76\u003c\/p\u003e \u003cp\u003e3.3 Measures of Shape 78\u003c\/p\u003e \u003cp\u003e3.4 Business Analytics Using Descriptive Statistics 81\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 84\u003c\/p\u003e \u003cp\u003eEthical Considerations 84\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Coca-Cola Develops the African Market 89\u003c\/p\u003e \u003cp\u003eBig Data Case 91\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Probability 92\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Equity of the Sexes in the Workplace 92\u003c\/p\u003e \u003cp\u003e4.1 Introduction to Probability 93\u003c\/p\u003e \u003cp\u003e4.2 Structure of Probability 96\u003c\/p\u003e \u003cp\u003e4.3 Marginal, Union, Joint, and Conditional Probabilities 101\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 102\u003c\/p\u003e \u003cp\u003e4.4 Addition Laws 103\u003c\/p\u003e \u003cp\u003e4.5 Multiplication Laws 110\u003c\/p\u003e \u003cp\u003e4.6 Conditional Probability 115\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 118\u003c\/p\u003e \u003cp\u003e4.7 Revision of Probabilities: Bayes’ Rule 121\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 125\u003c\/p\u003e \u003cp\u003eEthical Considerations 126\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Colgate-Palmolive Makes a “Total” Effort 131\u003c\/p\u003e \u003cp\u003eBig Data Case 131\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 \u003c\/b\u003e\u003cb\u003eDiscrete Distributions 132\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Life with a Cell Phone 132\u003c\/p\u003e \u003cp\u003e5.1 Discrete Versus Continuous Distributions 133\u003c\/p\u003e \u003cp\u003e5.2 Describing a Discrete Distribution 135\u003c\/p\u003e \u003cp\u003e5.3 Binomial Distribution 138\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 147\u003c\/p\u003e \u003cp\u003e5.4 Poisson Distribution 149\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 153\u003c\/p\u003e \u003cp\u003e5.5 Hypergeometric Distribution 157\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 161\u003c\/p\u003e \u003cp\u003eEthical Considerations 162\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Whole Foods Market Grows Through Mergers and Acquisitions 168\u003c\/p\u003e \u003cp\u003eBig Data Case 168\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 \u003c\/b\u003e\u003cb\u003eContinuous Distributions 169\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: CSX Corporation 169\u003c\/p\u003e \u003cp\u003e6.1 The Uniform Distribution 171\u003c\/p\u003e \u003cp\u003e6.2 Normal Distribution 175\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 185\u003c\/p\u003e \u003cp\u003e6.3 Using the Normal Curve to Approximate Binomial Distribution Problems 187\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 193\u003c\/p\u003e \u003cp\u003e6.4 Exponential Distribution 194\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 197\u003c\/p\u003e \u003cp\u003eEthical Considerations 198\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: USAA 203\u003c\/p\u003e \u003cp\u003eBig Data Case 203\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 \u003c\/b\u003e\u003cb\u003eSampling and Sampling Distributions 205\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Toro 205\u003c\/p\u003e \u003cp\u003e7.1 Sampling 206\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 208\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 214\u003c\/p\u003e \u003cp\u003e7.2 Sampling Distribution of x̄ 217\u003c\/p\u003e \u003cp\u003e7.3 Sampling Distribution of p 227\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 230\u003c\/p\u003e \u003cp\u003eEthical Considerations 230\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: 3M 234\u003c\/p\u003e \u003cp\u003eBig Data Case 235\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 \u003c\/b\u003e\u003cb\u003eStatistical Inference: Estimation for Single Populations 236\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Batteries and Bulbs: How Long Do They Last? 236\u003c\/p\u003e \u003cp\u003e8.1 Estimating the Population Mean Using the \u003ci\u003ez \u003c\/i\u003eStatistic (σ Known) 238\u003c\/p\u003e \u003cp\u003e8.2 Estimating the Population Mean Using the \u003ci\u003et \u003c\/i\u003eStatistic (σ Unknown) 245\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 250\u003c\/p\u003e \u003cp\u003e8.3 Estimating the Population Proportion 251\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 252\u003c\/p\u003e \u003cp\u003e8.4 Estimating the Population Variance 255\u003c\/p\u003e \u003cp\u003e8.5 Estimating Sample Size 259\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 262\u003c\/p\u003e \u003cp\u003eEthical Considerations 263\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: The Container Store 267\u003c\/p\u003e \u003cp\u003eBig Data Case 268\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Statistical Inference: Hypothesis Testing for Single Populations 269\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Valero Energy 269\u003c\/p\u003e \u003cp\u003e9.1 Introduction to Hypothesis Testing 270\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 273\u003c\/p\u003e \u003cp\u003e9.2 Testing Hypotheses About a Population Mean Using the \u003ci\u003ez\u003c\/i\u003e Statistic (σ Known) 279\u003c\/p\u003e \u003cp\u003e9.3 Testing Hypotheses About a Population Mean Using the \u003ci\u003et\u003c\/i\u003e Statistic (σ Unknown) 287\u003c\/p\u003e \u003cp\u003e9.4 Testing Hypotheses About a Proportion 294\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 297\u003c\/p\u003e \u003cp\u003e9.5 Testing Hypotheses About a Variance 300\u003c\/p\u003e \u003cp\u003e9.6 Solving for Type II Errors 303\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 311\u003c\/p\u003e \u003cp\u003eEthical Considerations 312\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Frito-Lay Targets the Hispanic Market 316\u003c\/p\u003e \u003cp\u003eBig Data Case 317\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 \u003c\/b\u003e\u003cb\u003eStatistical Inferences About Two Populations 318\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: L. L. Bean 318\u003c\/p\u003e \u003cp\u003e10.1 Hypothesis Testing and Confidence Intervals About the Difference in Two Means Using the \u003ci\u003ez \u003c\/i\u003eStatistic (Population Variances Known) 321\u003c\/p\u003e \u003cp\u003e10.2 Hypothesis Testing and Confidence Intervals About the Difference in Two Means: Independent Samples and Population Variances Unknown 329\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 337\u003c\/p\u003e \u003cp\u003e10.3 Statistical Inferences for Two Related Populations 339\u003c\/p\u003e \u003cp\u003e10.4 Statistical Inferences About Two Population Proportions, \u003ci\u003ep\u003c\/i\u003e\u003csub\u003e1\u003c\/sub\u003e − \u003ci\u003ep\u003c\/i\u003e\u003csub\u003e2\u003c\/sub\u003e 348\u003c\/p\u003e \u003cp\u003e10.5 Testing Hypotheses About Two Population Variances 355\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 363\u003c\/p\u003e \u003cp\u003eEthical Considerations 364\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Five Guys 370\u003c\/p\u003e \u003cp\u003eBig Data Case 371\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 \u003c\/b\u003e\u003cb\u003eAnalysis of Variance and Design of Experiments 372\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Job and Career Satisfaction of Foreign Self-Initiated Expatriates 372\u003c\/p\u003e \u003cp\u003e11.1 Introduction to Design of Experiments 373\u003c\/p\u003e \u003cp\u003e11.2 The Completely Randomized Design (One-Way ANOVA) 376\u003c\/p\u003e \u003cp\u003e11.3 Multiple Comparison Tests 387\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 395\u003c\/p\u003e \u003cp\u003e11.4 The Randomized Block Design 396\u003c\/p\u003e \u003cp\u003e11.5 A Factorial Design (Two-Way ANOVA) 405\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 418\u003c\/p\u003e \u003cp\u003eEthical Considerations 419\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: The Clarkson Company: A Division of Tyco International 425\u003c\/p\u003e \u003cp\u003eBig Data Case 426\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 \u003c\/b\u003e\u003cb\u003eSimple Regression Analysis and Correlation 427\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Predicting International Hourly Wages by the Price of a Big Mac 427\u003c\/p\u003e \u003cp\u003e12.1 Correlation 428\u003c\/p\u003e \u003cp\u003e12.2 Introduction to Simple Regression Analysis 432\u003c\/p\u003e \u003cp\u003e12.3 Determining the Equation of the Regression Line 433\u003c\/p\u003e \u003cp\u003e12.4 Residual Analysis 439\u003c\/p\u003e \u003cp\u003e12.5 Standard Error of the Estimate 446\u003c\/p\u003e \u003cp\u003e12.6 Coefficient of Determination 449\u003c\/p\u003e \u003cp\u003e12.7 Hypothesis Tests for the Slope of the Regression Model and Testing the Overall Model 451\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 453\u003c\/p\u003e \u003cp\u003e12.8 Estimation 456\u003c\/p\u003e \u003cp\u003e12.9 Using Regression to Develop a Forecasting Trend Line 460\u003c\/p\u003e \u003cp\u003e12.10 Interpreting the Output 466\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 468\u003c\/p\u003e \u003cp\u003eEthical Considerations 469\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Caterpillar, Inc. 475\u003c\/p\u003e \u003cp\u003eBig Data Case 476\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 \u003c\/b\u003e\u003cb\u003eMultiple Regression Analysis 477\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Are You Going to Hate Your New Job? 477\u003c\/p\u003e \u003cp\u003e13.1 The Multiple Regression Model 478\u003c\/p\u003e \u003cp\u003e13.2 Significance Tests of the Regression Model and Its Coefficients 485\u003c\/p\u003e \u003cp\u003e13.3 Residuals, Standard Error of the Estimate, and \u003ci\u003eR\u003c\/i\u003e\u003csup\u003e2\u003c\/sup\u003e 489\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 494\u003c\/p\u003e \u003cp\u003e13.4 Interpreting Multiple Regression Computer Output 495\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 497\u003c\/p\u003e \u003cp\u003eEthical Considerations 498\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003cbr\u003e\u003cbr\u003eChapter Case: Starbucks Introduces Debit Card 502\u003c\/p\u003e \u003cp\u003eBig Data Case 503\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 \u003c\/b\u003e\u003cb\u003eBuilding Multiple Regression Models 504\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Predicting CEO Salaries 504\u003c\/p\u003e \u003cp\u003e14.1 Nonlinear Models: Mathematical Transformation 505\u003c\/p\u003e \u003cp\u003e14.2 Indicator (Dummy) Variables 518\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 521\u003c\/p\u003e \u003cp\u003e14.3 Model-Building: Search Procedures 522\u003c\/p\u003e \u003cp\u003e14.4 Multicollinearity 532\u003c\/p\u003e \u003cp\u003e14.5 Logistic Regression 535\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 542\u003c\/p\u003e \u003cp\u003eEthical Considerations 543\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Virginia Semiconductor 548\u003c\/p\u003e \u003cp\u003eBig Data Case 550\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 \u003c\/b\u003e\u003cb\u003eTime-Series Forecasting and Index Numbers 551\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Forecasting Air Pollution 551\u003c\/p\u003e \u003cp\u003e15.1 Introduction to Forecasting 552\u003c\/p\u003e \u003cp\u003e15.2 Smoothing Techniques 557\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 566\u003c\/p\u003e \u003cp\u003e15.3 Trend Analysis 567\u003c\/p\u003e \u003cp\u003e15.4 Seasonal Effects 574\u003c\/p\u003e \u003cp\u003e15.5 Autocorrelation and Autoregression 581\u003c\/p\u003e \u003cp\u003e15.6 Index Numbers 587\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 594\u003c\/p\u003e \u003cp\u003eEthical Considerations 596\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Debourgh Manufacturing Company 602\u003c\/p\u003e \u003cp\u003eBig Data Case 604\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 \u003c\/b\u003e\u003cb\u003eAnalysis of Categorical Data 605\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Selecting Suppliers in the Electronics Industry 605\u003c\/p\u003e \u003cp\u003e16.1 Chi-Square Goodness-of-Fit Test 606\u003c\/p\u003e \u003cp\u003e16.2 Contingency Analysis: Chi-Square Test of Independence 613\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 619\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 620\u003c\/p\u003e \u003cp\u003eEthical Considerations 620\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics \u003c\/p\u003e \u003cp\u003eChapter Case: Foot Locker in the Shoe Mix 623\u003c\/p\u003e \u003cp\u003eBig Data Case 624\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 \u003c\/b\u003e\u003cb\u003eNonparametric Statistics 625\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: How is the Doughnut Business? 625\u003c\/p\u003e \u003cp\u003e17.1 Runs Test 628\u003c\/p\u003e \u003cp\u003e17.2 Mann-Whitney \u003ci\u003eU \u003c\/i\u003eTest 632\u003c\/p\u003e \u003cp\u003e17.3 Wilcoxon Matched-Pairs Signed Rank Test 639\u003c\/p\u003e \u003cp\u003e17.4 Kruskal-Wallis Test 647\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 651\u003c\/p\u003e \u003cp\u003e17.5 Friedman Test 651\u003c\/p\u003e \u003cp\u003e17.6 Spearman’s Rank Correlation 656\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 659\u003c\/p\u003e \u003cp\u003eEthical Considerations 660\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Schwinn 666\u003c\/p\u003e \u003cp\u003eBig Data Case 667\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 \u003c\/b\u003e\u003cb\u003eStatistical Quality Control 668\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Italy’s Piaggio Makes a Comeback 668\u003c\/p\u003e \u003cp\u003e18.1 Introduction to Quality Control 669\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 678\u003c\/p\u003e \u003cp\u003e18.2 Process Analysis 679\u003c\/p\u003e \u003cp\u003e18.3 Control Charts 686\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 701\u003c\/p\u003e \u003cp\u003eEthical Considerations 702\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Standard Motor Products 708\u003c\/p\u003e \u003cp\u003eBig Data Case 709\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 \u003c\/b\u003e\u003cb\u003eDecision Analysis 710\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Dilemma: Decision-making at the CEO Level 710\u003c\/p\u003e \u003cp\u003e19.1 The Decision Table and Decision-making Under Certainty 711\u003c\/p\u003e \u003cp\u003e19.2 Decision-making Under Uncertainty 713\u003c\/p\u003e \u003cp\u003eThinking Critically About Statistics in Business Today 717\u003c\/p\u003e \u003cp\u003e19.3 Decision-making Under Risk 720\u003c\/p\u003e \u003cp\u003e19.4 Revising Probabilities in Light of Sample Information 729\u003c\/p\u003e \u003cp\u003eDecision Dilemma Solved 737\u003c\/p\u003e \u003cp\u003eEthical Considerations 737\u003c\/p\u003e \u003cp\u003eSummary \/ Key Terms \/ Formulas \/ Supplementary Problems \/ Exploring the Databases with Business Analytics\u003c\/p\u003e \u003cp\u003eChapter Case: Fletcher-Terry: On The Cutting Edge 741\u003c\/p\u003e \u003cp\u003eBig Data Case 742\u003c\/p\u003e \u003cp\u003eAppendix A Tables 743\u003c\/p\u003e \u003cp\u003eAppendix B Answers to Selected Odd-Numbered Quantitative Problems 784\u003c\/p\u003e \u003cp\u003eGlossary 793\u003c\/p\u003e \u003cp\u003eIndex 801\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407114182999,"sku":"9781119668015","price":54.89,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119668015.jpg?v=1730498230","url":"https:\/\/bookcurl.com\/products\/business-statistics-9781119668015","provider":"Book Curl","version":"1.0","type":"link"}