Basic Statistics for Business & Economics, Tenth Edition
By Douglas A Lind, William G Marchal and Samuel A Wathen
Contents:
A Note from the Authors vi
1. What Is Statistics? 1
Introduction 2
Why Study Statistics? 2
What Is Meant by Statistics? 3
Types of Statistics 4
Descriptive Statistics 4
Inferential Statistics 5
Types of Variables 6
Levels of Measurement 7
Nominal-Level Data 7
Ordinal-Level Data 8
Interval-Level Data 9
Ratio-Level Data 10
EXERCISES 11
Ethics and Statistics 12
Basic Business Analytics 12
Chapter Summary 14
Chapter Exercises 14
Data Analytics 17
Practice Test 17
2. Describing Data: FREQUENCY TABLES, FREQUENCY DISTRIBUTIONS, AND GRAPHIC PRESENTATION 19
Introduction 20
Constructing Frequency Tables 20
Relative Class Frequencies 21
Graphic Presentation of Qualitative Data 22
EXERCISES 26
Constructing Frequency Distributions 27
Relative Frequency Distribution 31
EXERCISES 32
Graphic Presentation of a Distribution 33
Histogram 33
Frequency Polygon 36
EXERCISES 38
Cumulative Distributions 39
EXERCISES 42
Chapter Summary 43
Chapter Exercises 44
Data Analytics 51
Practice Test 51
3. Describing Data: NUMERICAL MEASURES 53
Introduction 54
Measures of Location 54
The Population Mean 55
The Sample Mean 56
Properties of the Arithmetic Mean 57
EXERCISES 58
The Median 59
The Mode 61
Software Solution 63
EXERCISES 63
The Relative Positions of the Mean, Median, and Mode 65
EXERCISES 67
The Weighted Mean 67
EXERCISES 69
Why Study Dispersion? 69
Range 70
Variance 70
EXERCISES 72
Population Variance 73
Population Standard Deviation 75
EXERCISES 76
Sample Variance and Standard Deviation 76
Software Solution 78
EXERCISES 78
Interpretation and Uses of the Standard Deviation 79
Chebyshev’s Theorem 79
The Empirical Rule 79
EXERCISES 81
Ethics and Reporting Results 81
Chapter Summary 82
Chapter Exercises 83
Data Analytics 87
Practice Test 87
4. Describing Data DISPLAYING AND EXPLORING DATA 89
Introduction 90
Dot Plots 90
EXERCISES 92
Measures of Position 93
Quartiles, Deciles, and Percentiles 93
EXERCISES 97
Box Plots 97
EXERCISES 100
Skewness 101
EXERCISES 104
Describing the Relationship between Two Variables 105
Correlation Coefficient 106
Contingency Tables 108
EXERCISES 110
Chapter Summary 111
Chapter Exercises 112
Data Analytics 117
Practice Test 118
5. A Survey of Probability Concepts 119
Introduction 120
What Is a Probability? 121
Approaches to Assigning Probabilities 123
Classical Probability 123
Empirical Probability 124
Subjective Probability 126
EXERCISES 127
Rules of Addition for Computing Probabilities 128
Special Rule of Addition 128
Complement Rule 130
The General Rule of Addition 131
EXERCISES 133
Rules of Multiplication to Calculate Probability 134
Special Rule of Multiplication 134
General Rule of Multiplication 136
Contingency Tables 137
Tree Diagrams 141
EXERCISES 143
Principles of Counting 144
The Multiplication Formula 144
The Permutation Formula 146
The Combination Formula 148
EXERCISES 149
Chapter Summary 150
Chapter Exercises 151
Data Analytics 156
Practice Test 157
6. Discrete Probability Distributions 158
Introduction 159
What Is a Probability Distribution? 159
Random Variables 161
Discrete Random Variable 162
Continuous Random Variable 163
The Mean, Variance, and Standard Deviation of a Discrete
Probability Distribution 163
Mean 163
Variance and Standard Deviation 164
EXERCISES 166
Binomial Probability Distribution 167
How Is a Binomial Probability Computed? 169
Binomial Probability Tables 171
EXERCISES 174
Cumulative Binomial Probability Distributions 175
EXERCISES 177
Poisson Probability Distribution 177
EXERCISES 182
Chapter Summary 182
Chapter Exercises 183
Data Analytics 187
Practice Test 187
7. Continuous Probability Distributions 189
Introduction 190
The Family of Uniform Probability Distributions 190
EXERCISES 193
The Family of Normal Probability Distributions 194
The Standard Normal Probability Distribution 197
Applications of the Standard Normal Distribution 198
The Empirical Rule 198
EXERCISES 200
Finding Areas under the Normal Curve 201
EXERCISES 204
EXERCISES 206
EXERCISES 209
Chapter Summary 209
Chapter Exercises 210
Data Analytics 213
Practice Test 214
8. Sampling, Sampling Methods, and the Central Limit Theorem 215
Introduction 216
Research and Sampling 216
Sampling Methods 217
Simple Random Sampling 217
Systematic Random Sampling 220
Stratified Random Sampling 221
Cluster Sampling 222
EXERCISES 223
Sample Mean as a Random Variable 225
Sampling Distribution of the Sample Mean 226
EXERCISES 230
The Central Limit Theorem 231
Standard Error of the Mean 237
EXERCISES 237
Using the Sampling Distribution of the Sample Mean 239
EXERCISES 241
Chapter Summary 241
Chapter Exercises 242
Data Analytics 247
Practice Test 248
9. Estimation and Confidence Intervals 249
Introduction 250
Point Estimate for a Population Mean 250
Confidence Intervals for a Population Mean 251
Population Standard Deviation, Known σ 251
A Computer Simulation 256
EXERCISES 258
Population Standard Deviation, σ Unknown 259
EXERCISES 266
A Confidence Interval for a Population Proportion 267
EXERCISES 270
Choosing an Appropriate Sample Size 270
Sample Size to Estimate a Population Mean 271
Sample Size to Estimate a Population Proportion 272
EXERCISES 274
Chapter Summary 274
Chapter Exercises 275
Data Analytics 279
Practice Test 280
10. One-Sample Tests of Hypothesis 281
Introduction 282
What Is Hypothesis Testing? 282
Six-Step Procedure for Testing a Hypothesis 283
Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1) 283
Step 2: Select a Level of Significance 284
Step 3: Select the Test Statistic 286
Step 4: Formulate the Decision Rule 286
Step 5: Make a Decision 287
Step 6: Interpret the Result 287
One-Tailed and Two-Tailed Hypothesis Tests 288
Hypothesis Testing for a Population Mean: Known Population Standard Deviation 290
A Two-Tailed Test 290
A One-Tailed Test 293
p-Value in Hypothesis Testing 294
EXERCISES 296
Hypothesis Testing for a Population Mean: Population Standard Deviation Unknown 297
EXERCISES 300
A Statistical Software Solution 301
EXERCISES 303
Chapter Summary 304
Chapter Exercises 305
Data Analytics 308
Practice Test 309
11. Two-Sample Tests of Hypothesis 310
Introduction 311
Two-Sample Tests of Hypothesis: Independent Samples 311
EXERCISES 316
Comparing Population Means with Unknown Population Standard Deviations 317
Two-Sample Pooled Test 317
EXERCISES 321
Unequal Population Standard Deviations 323
EXERCISES 326
Two-Sample Tests of Hypothesis: Dependent Samples 327
Comparing Dependent and Independent Samples 330
EXERCISES 333
Chapter Summary 334
Chapter Exercises 336
Data Analytics 344
Practice Test 345
12. Analysis of Variance 346
Introduction 347
Comparing Two Population Variances 347
The F-Distribution 347
Testing a Hypothesis of Equal Population Variances 348
EXERCISES 352
ANOVA: Analysis of Variance 352
ANOVA Assumptions 353
The ANOVA Test 354
EXERCISES 361
Inferences about Pairs of Treatment Means 362
EXERCISES 365
Chapter Summary 367
Chapter Exercises 368
Data Analytics 375
Practice Test 376
13. Correlation and Linear Regression 13
Introduction 379
What Is Correlation Analysis? 379
The Correlation Coefficient 382
EXERCISES 387
Testing the Significance of the Correlation Coefficient 389
EXERCISES 392
Regression Analysis 393
Least Squares Principle 393
Drawing the Regression Line 396
EXERCISES 399
Testing the Significance of the Slope 401
EXERCISES 403
Evaluating a Regression Equation’s Ability to Predict 404
The Standard Error of Estimate 404
The Coefficient of Determination 405
EXERCISES 406
Relationships among the Correlation Coefficient, the Coefficient of Determination, and the Standard Error of
Estimate 406
EXERCISES 408
Interval Estimates of Prediction 409
Assumptions Underlying Linear Regression 409
Constructing Confidence and Prediction Intervals 410
EXERCISES 413
Transforming Data 413
EXERCISES 416
Chapter Summary 418
Chapter Exercises 420
Data Analytics 429
Practice Test 430
14. Multiple Regression Analysis 431
Introduction 432
Multiple Regression Analysis 432
EXERCISES 436
Evaluating a Multiple Regression Equation 438
The ANOVA Table 438
Multiple Standard Error of Estimate 439
Coefficient of Multiple Determination 440
Adjusted Coefficient of Determination 441
EXERCISES 442
Inferences in Multiple Linear Regression 442
Global Test: Testing the Multiple Regression Model 442
Evaluating Individual Regression Coefficients 445
EXERCISES 448
Evaluating the Assumptions of Multiple Regression 449
Linear Relationship 450
Variation in Residuals Same for Large and Small ŷ Values 451
Distribution of Residuals 452
Multicollinearity 452
Independent Observations 454
Qualitative Independent Variables 455
Stepwise Regression 458
EXERCISES 460
Review of Multiple Regression 461
Chapter Summary 467
Chapter Exercises 469
Data Analytics 479
Practice Test 480
Appendix A:
Appendix B:
Appendix C:
15. Nonparametric Methods: NOMINAL LEVEL HYPOTHESIS TESTS 482
Introduction 483
Test a Hypothesis of a Population Proportion 483
EXERCISES 486
Two-Sample Tests about Proportions 487
EXERCISES 491
Goodness-of-Fit Tests: Comparing Observed and
Expected Frequency Distributions 492
Hypothesis Test of Equal Expected Frequencies 492
EXERCISES 497
Hypothesis Test of Unequal Expected Frequencies 499
Limitations of Chi-Square 500
EXERCISES 502
Contingency Table Analysis 503
EXERCISES 506
Chapter Summary 507
Chapter Exercises 508
Data Analytics 513
Practice Test 514
APPENDIXES 515
Data Sets 516
Tables 524
Answers to Odd-Numbered Chapter Exercises & Solutions to Practice Test 537
Appendix D:Answers to Self-Review 580
Glossary 589
Index 593
Key Formulas 605
Areas under the Normal Curve 609