Statistics for Business and Economics (11th Edition) by David R. Anderson, Dennis J. Sweeney, Thomas A. Williams PDF

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Summary

CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION Entries in this table give the area under the curve to the left of the Cumulative z value. For example, for probability z = –.85, the cumulative probability is .1977. z 0 z .00 .01 .02 .03 .04 .05 .06 .07 .08 .09 3.0 .0013 .0013 .0013 ....

Description

CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION

Entries in this table give the area under the curve to the left of the z value. For example, for z = –.85, the cumulative probability is .1977.

Cumulative probability

z

0

z

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

⫺3.0

.0013

.0013

.0013

.0012

.0012

.0011

.0011

.0011

.0010

.0010

⫺2.9 ⫺2.8 ⫺2.7 ⫺2.6 ⫺2.5

.0019 .0026 .0035 .0047 .0062

.0018 .0025 .0034 .0045 .0060

.0018 .0024 .0033 .0044 .0059

.0017 .0023 .0032 .0043 .0057

.0016 .0023 .0031 .0041 .0055

.0016 .0022 .0030 .0040 .0054

.0015 .0021 .0029 .0039 .0052

.0015 .0021 .0028 .0038 .0051

.0014 .0020 .0027 .0037 .0049

.0014 .0019 .0026 .0036 .0048

⫺2.4 ⫺2.3 ⫺2.2 ⫺2.1 ⫺2.0

.0082 .0107 .0139 .0179 .0228

.0080 .0104 .0136 .0174 .0222

.0078 .0102 .0132 .0170 .0217

.0075 .0099 .0129 .0166 .0212

.0073 .0096 .0125 .0162 .0207

.0071 .0094 .0122 .0158 .0202

.0069 .0091 .0119 .0154 .0197

.0068 .0089 .0116 .0150 .0192

.0066 .0087 .0113 .0146 .0188

.0064 .0084 .0110 .0143 .0183

⫺1.9 ⫺1.8 ⫺1.7 ⫺1.6 ⫺1.5

.0287 .0359 .0446 .0548 .0668

.0281 .0351 .0436 .0537 .0655

.0274 .0344 .0427 .0526 .0643

.0268 .0336 .0418 .0516 .0630

.0262 .0329 .0409 .0505 .0618

.0256 .0322 .0401 .0495 .0606

.0250 .0314 .0392 .0485 .0594

.0244 .0307 .0384 .0475 .0582

.0239 .0301 .0375 .0465 .0571

.0233 .0294 .0367 .0455 .0559

⫺1.4 ⫺1.3 ⫺1.2 ⫺1.1 ⫺1.0

.0808 .0968 .1151 .1357 .1587

.0793 .0951 .1131 .1335 .1562

.0778 .0934 .1112 .1314 .1539

.0764 .0918 .1093 .1292 .1515

.0749 .0901 .1075 .1271 .1492

.0735 .0885 .1056 .1251 .1469

.0721 .0869 .1038 .1230 .1446

.0708 .0853 .1020 .1210 .1423

.0694 .0838 .1003 .1190 .1401

.0681 .0823 .0985 .1170 .1379

⫺.9 ⫺.8 ⫺.7 ⫺.6 ⫺.5

.1841 .2119 .2420 .2743 .3085

.1814 .2090 .2389 .2709 .3050

.1788 .2061 .2358 .2676 .3015

.1762 .2033 .2327 .2643 .2981

.1736 .2005 .2296 .2611 .2946

.1711 .1977 .2266 .2578 .2912

.1685 .1949 .2236 .2546 .2877

.1660 .1922 .2206 .2514 .2843

.1635 .1894 .2177 .2483 .2810

.1611 .1867 .2148 .2451 .2776

⫺.4 ⫺.3 ⫺.2 ⫺.1 ⫺.0

.3446 .3821 .4207 .4602 .5000

.3409 .3783 .4168 .4562 .4960

.3372 .3745 .4129 .4522 .4920

.3336 .3707 .4090 .4483 .4880

.3300 .3669 .4052 .4443 .4840

.3264 .3632 .4013 .4404 .4801

.3228 .3594 .3974 .4364 .4761

.3192 .3557 .3936 .4325 .4721

.3156 .3520 .3897 .4286 .4681

.3121 .3483 .3859 .4247 .4641

CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION

Cumulative probability

0

Entries in the table give the area under the curve to the left of the z value. For example, for z = 1.25, the cumulative probability is .8944.

z

z

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.0 .1 .2 .3 .4

.5000 .5398 .5793 .6179 .6554

.5040 .5438 .5832 .6217 .6591

.5080 .5478 .5871 .6255 .6628

.5120 .5517 .5910 .6293 .6664

.5160 .5557 .5948 .6331 .6700

.5199 .5596 .5987 .6368 .6736

.5239 .5636 .6026 .6406 .6772

.5279 .5675 .6064 .6443 .6808

.5319 .5714 .6103 .6480 .6844

.5359 .5753 .6141 .6517 .6879

.5 .6 .7 .8 .9

.6915 .7257 .7580 .7881 .8159

.6950 .7291 .7611 .7910 .8186

.6985 .7324 .7642 .7939 .8212

.7019 .7357 .7673 .7967 .8238

.7054 .7389 .7704 .7995 .8264

.7088 .7422 .7734 .8023 .8289

.7123 .7454 .7764 .8051 .8315

.7157 .7486 .7794 .8078 .8340

.7190 .7517 .7823 .8106 .8365

.7224 .7549 .7852 .8133 .8389

1.0 1.1 1.2 1.3 1.4

.8413 .8643 .8849 .9032 .9192

.8438 .8665 .8869 .9049 .9207

.8461 .8686 .8888 .9066 .9222

.8485 .8708 .8907 .9082 .9236

.8508 .8729 .8925 .9099 .9251

.8531 .8749 .8944 .9115 .9265

.8554 .8770 .8962 .9131 .9279

.8577 .8790 .8980 .9147 .9292

.8599 .8810 .8997 .9162 .9306

.8621 .8830 .9015 .9177 .9319

1.5 1.6 1.7 1.8 1.9

.9332 .9452 .9554 .9641 .9713

.9345 .9463 .9564 .9649 .9719

.9357 .9474 .9573 .9656 .9726

.9370 .9484 .9582 .9664 .9732

.9382 .9495 .9591 .9671 .9738

.9394 .9505 .9599 .9678 .9744

.9406 .9515 .9608 .9686 .9750

.9418 .9525 .9616 .9693 .9756

.9429 .9535 .9625 .9699 .9761

.9441 .9545 .9633 .9706 .9767

2.0 2.1 2.2 2.3 2.4

.9772 .9821 .9861 .9893 .9918

.9778 .9826 .9864 .9896 .9920

.9783 .9830 .9868 .9898 .9922

.9788 .9834 .9871 .9901 .9925

.9793 .9838 .9875 .9904 .9927

.9798 .9842 .9878 .9906 .9929

.9803 .9846 .9881 .9909 .9931

.9808 .9850 .9884 .9911 .9932

.9812 .9854 .9887 .9913 .9934

.9817 .9857 .9890 .9916 .9936

2.5 2.6 2.7 2.8 2.9

.9938 .9953 .9965 .9974 .9981

.9940 .9955 .9966 .9975 .9982

.9941 .9956 .9967 .9976 .9982

.9943 .9957 .9968 .9977 .9983

.9945 .9959 .9969 .9977 .9984

.9946 .9960 .9970 .9978 .9984

.9948 .9961 .9971 .9979 .9985

.9949 .9962 .9972 .9979 .9985

.9951 .9963 .9973 .9980 .9986

.9952 .9964 .9974 .9981 .9986

3.0

.9987

.9987

.9987

.9988

.9988

.9989

.9989

.9989

.9990

.9990

STATISTICS FOR BUSINESS AND ECONOMICS 11e

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STATISTICS FOR BUSINESS AND ECONOMICS 11e David R. Anderson University of Cincinnati

Dennis J. Sweeney University of Cincinnati

Thomas A. Williams Rochester Institute of Technology

Statistics for Business and Economics, Eleventh Edition David R. Anderson, Dennis J. Sweeney, Thomas A. Williams VP/Editorial Director: Jack W. Calhoun Publisher: Joe Sabatino Senior Acquisitions Editor: Charles McCormick, Jr. Developmental Editor: Maggie Kubale Editorial Assistant: Nora Heink Marketing Communications Manager: Libby Shipp Content Project Manager: Jacquelyn K Featherly Media Editor: Chris Valentine Manufacturing Coordinator: Miranda Kipper

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Brief Contents

Preface xxv About the Authors xxix Chapter 1 Data and Statistics 1 Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations 31 Chapter 3 Descriptive Statistics: Numerical Measures 85 Chapter 4 Introduction to Probability 148 Chapter 5 Discrete Probability Distributions 193 Chapter 6 Continuous Probability Distributions 232 Chapter 7 Sampling and Sampling Distributions 265 Chapter 8 Interval Estimation 308 Chapter 9 Hypothesis Tests 348 Chapter 10 Inference About Means and Proportions with Two Populations 406 Chapter 11 Inferences About Population Variances 448 Chapter 12 Tests of Goodness of Fit and Independence 472 Chapter 13 Experimental Design and Analysis of Variance 506 Chapter 14 Simple Linear Regression 560 Chapter 15 Multiple Regression 642 Chapter 16 Regression Analysis: Model Building 712 Chapter 17 Index Numbers 763 Chapter 18 Time Series Analysis and Forecasting 784 Chapter 19 Nonparametric Methods 855 Chapter 20 Statistical Methods for Quality Control 903 Chapter 21 Decision Analysis 937 Chapter 22 Sample Survey On Website Appendix A References and Bibliography 976 Appendix B Tables 978 Appendix C Summation Notation 1005 Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises 1007 Appendix E Using Excel Functions 1062 Appendix F Computing p-Values Using Minitab and Excel 1067 Index 1071

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Contents

Preface xxv About the Authors xxix

Chapter 1 Data and Statistics 1 Statistics in Practice: BusinessWeek 2 1.1 Applications in Business and Economics 3 Accounting 3 Finance 4 Marketing 4 Production 4 Economics 4 1.2 Data 5 Elements, Variables, and Observations 5 Scales of Measurement 6 Categorical and Quantitative Data 7 Cross-Sectional and Time Series Data 7 1.3 Data Sources 10 Existing Sources 10 Statistical Studies 11 Data Acquisition Errors 13 1.4 Descriptive Statistics 13 1.5 Statistical Inference 15 1.6 Computers and Statistical Analysis 17 1.7 Data Mining 17 1.8 Ethical Guidelines for Statistical Practice 18 Summary 20 Glossary 20 Supplementary Exercises 21 Appendix: An Introduction to StatTools 28

Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations 31 Statistics in Practice: Colgate-Palmolive Company 32 2.1 Summarizing Categorical Data 33 Frequency Distribution 33 Relative Frequency and Percent Frequency Distributions 34 Bar Charts and Pie Charts 34

x

Contents

2.2 Summarizing Quantitative Data 39 Frequency Distribution 39 Relative Frequency and Percent Frequency Distributions 41 Dot Plot 41 Histogram 41 Cumulative Distributions 43 Ogive 44 2.3 Exploratory Data Analysis: The Stem-and-Leaf Display 48 2.4 Crosstabulations and Scatter Diagrams 53 Crosstabulation 53 Simpson’s Paradox 56 Scatter Diagram and Trendline 57 Summary 63 Glossary 64 Key Formulas 65 Supplementary Exercises 65 Case Problem 1: Pelican Stores 71 Case Problem 2: Motion Picture Industry 72 Appendix 2.1 Using Minitab for Tabular and Graphical Presentations 73 Appendix 2.2 Using Excel for Tabular and Graphical Presentations 75 Appendix 2.3 Using StatTools for Tabular and Graphical Presentations 84

Chapter 3 Descriptive Statistics: Numerical Measures 85 Statistics in Practice: Small Fry Design 86 3.1 Measures of Location 87 Mean 87 Median 88 Mode 89 Percentiles 90 Quartiles 91 3.2 Measures of Variability 95 Range 96 Interquartile Range 96 Variance 97 Standard Deviation 99 Coefficient of Variation 99 3.3 Measures of Distribution Shape, Relative Location, and Detecting Outliers 102 Distribution Shape 102 z-Scores 103 Chebyshev’s Theorem 104 Empirical Rule 105 Detecting Outliers 106

Contents

3.4 Exploratory Data Analysis 109 Five-Number Summary 109 Box Plot 110 3.5 Measures of Association Between Two Variables 115 Covariance 115 Interpretation of the Covariance 117 Correlation Coefficient 119 Interpretation of the Correlation Coefficient 120 3.6 The Weighted Mean and Working with Grouped Data 124 Weighted Mean 124 Grouped Data 125 Summary 129 Glossary 130 Key Formulas 131 Supplementary Exercises 133 Case Problem 1: Pelican Stores 137 Case Problem 2: Motion Picture Industry 138 Case Problem 3: Business Schools of Asia-Pacific 139 Case Problem 4: Heavenly Chocolates Website Transactions 139 Appendix 3.1 Descriptive Statistics Using Minitab 142 Appendix 3.2 Descriptive Statistics Using Excel 143 Appendix 3.3 Descriptive Statistics Using StatTools 146

Chapter 4 Introduction to Probability 148 Statistics in Practice: Oceanwide Seafood 149 4.1 Experiments, Counting Rules, and Assigning Probabilities 150 Counting Rules, Combinations, and Permutations 151 Assigning Probabilities 155 Probabilities for the KP&L Project 157 4.2 Events and Their Probabilities 160 4.3 Some Basic Relationships of Probability 164 Complement of an Event 164 Addition Law 165 4.4 Conditional Probability 171 Independent Events 174 Multiplication Law 174 4.5 Bayes’ Theorem 178 Tabular Approach 182 Summary 184 Glossary 184

xi

xii

Contents

Key Formulas 185 Supplementary Exercises 186 Case Problem: Hamilton County Judges 190

Chapter 5 Discrete Probability Distributions 193 Statistics in Practice: Citibank 194 5.1 Random Variables 194 Discrete Random Variables 195 Continuous Random Variables 196 5.2 Discrete Probability Distributions 197 5.3 Expected Value and Variance 202 Expected Value 202 Variance 203 5.4 Binomial Probability Distribution 207 A Binomial Experiment 208 Martin Clothing Store Problem 209 Using Tables of Binomial Probabilities 213 Expected Value and Variance for the Binomial Distribution 214 5.5 Poisson Probability Distribution 218 An Example Involving Time Intervals 218 An Example Involving Length or Distance Intervals 220 5.6 Hypergeometric Probability Distribution 221 Summary 225 Glossary 225 Key Formulas 226 Supplementary Exercises 227 Appendix 5.1 Discrete Probability Distributions with Minitab 230 Appendix 5.2 Discrete Probability Distributions with Excel 230

Chapter 6 Continuous Probability Distributions 232 Statistics in Practice: Procter & Gamble 233 6.1 Uniform Probability Distribution 234 Area as a Measure of Probability 235 6.2 Normal Probability Distribution 238 Normal Curve 238 Standard Normal Probability Distribution 240 Computing Probabilities for Any Normal Probability Distribution 245 Grear Tire Company Problem 246 6.3 Normal Approximation of Binomial Probabilities 250 6.4 Exponential Probability Distribution 253 Computing Probabilities for the Exponential Distribution 254 Relationship Between the Poisson and Exponential Distributions 255

Contents

Summary 257 Glossary 258 Key Formulas 258 Supplementary Exercises 258 Case Problem: Specialty Toys 261 Appendix 6.1 Continuous Probability Distributions with Minitab 262 Appendix 6.2 Continuous Probability Distributions with Excel 263

Chapter 7 Sampling and Sampling Distributions 265 Statistics in Practice: MeadWestvaco Corporation 266 7.1 The Electronics Associates Sampling Problem 267 7.2 Selecting a Sample 268 Sampling from a Finite Population 268 Sampling from an Infinite Population 270 7.3 Point Estimation 273 Practical Advice 275 7.4 Introduction to Sampling Distributions 276 _ 7.5 Sampling Distribution of x 278 _ Expected Value of x 279 _ Standard Deviation of x 280 _ Form of the Sampling Distribution of x 281 _ Sampling Distribution of x for the EAI Problem 283 _ Practical Value of the Sampling Distribution of x 283 Relationship Between the Sample Size and the Sampling _ Distribution of x 285 _ 7.6 Sampling Distribution of p 289 _ Expected Value of p 289 _ Standard Deviation of p 290 _ Form of the Sampling Distribution of p 291 _ Practical Value of the Sampling Distribution of p 291 7.7 Properties of Point Estimators 295 Unbiased 295 Efficiency 296 Consistency 297 7.8 Other Sampling Methods 297 Stratified Random Sampling 297 Cluster Sampling 298 Systematic Sampling 298 Convenience Sampling 299 Judgment Sampling 299 Summary 300 Glossary 300 Key Formulas 301

xiii

xiv

Contents

Supplementary Exercises 302 _ Appendix 7.1 The Expected Value and Standard Deviation of x 304 Appendix 7.2 Random Sampling with Minitab 306 Appendix 7.3 Random Sampling with Excel 306 Appendix 7.4 Random Sampling with StatTools 307

Chapter 8 Interval Estimation 308 Statistics in Practice: Food Lion 309 8.1 Population Mean: ␴ Known 310 Margin of Error and the Interval Estimate 310 Practical Advice 314 8.2 Population Mean: ␴ Unknown 316 Margin of Error and the Interval Estimate 317 Practical Advice 320 Using a Small Sample 320 Summary of Interval Estimation Procedures 322 8.3 Determining the Sample Size 325 8.4 Population Proportion 328 Determining the Sample Size 330 Summary 333 Glossary 334 Key Formulas 335 Supplementary Exercises 335 Case Problem 1: Young Professional Magazine 338 Case Problem 2: Gulf Real Estate Properties 339 Case Problem 3: Metropolitan Research, Inc. 341 Appendix 8.1 Interval Estimation with Minitab 341 Appendix 8.2 Interval Estimation with Excel 343 Appendix 8.3 Interval Estimation with StatTools 346

Chapter 9 Hypothesis Tests 348 Statistics in Practice: John Morrell & Company 349 9.1 Developing Null and Alternative Hypotheses 350 The Alternative Hypothesis as a Research Hypothesis 350 The Null Hypothesis as an Assumption to Be Challenged 351 Summary of Forms for Null and Alternative Hypotheses 352 9.2 Type I and Type II Errors 353 9.3 Population Mean: ␴ Known 356 One-Tailed Test 356 Two-Tailed Test 362 Summary and Practical Advice 365

xv

Contents

Relationship Between Interval Estimation and Hypothesis Testing 366 9.4 Population Mean: ␴ Unknown 370 One-Tailed Test 371 Two-Tailed Test 372 Summary and Practical Advice 373 9.5 Population Proportion 376 Summary 379 9.6 Hypothesis Testing and Decision Making 381 9.7 Calculating the Probability of Type II Errors 382 9.8 Determining the Sample Size for a Hypothesis Test About a Population Mean 387 Summary 391 Glossary 392 Key Formulas 392 Supplementary Exercises 393 Case Problem 1: Quality Associates, Inc. 396 Case Problem 2: Ethical Behavior of Business Students at Bayview University 397 Appendix 9.1 Hypothesis ...