Basic Statistics For Business & Economics, Ninth Edition
By Douglas A. Lind, William G. Marchal and Samuel A. Wathen
Contents:
A note from the Authors vi
Preface vii
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 13
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
EXERCISES 63
The Relative Positions of the Mean, Median, and Mode 64
EXERCISES 65
Software Solution 66
The Weighted Mean 67
EXERCISES 68
Why Study Dispersion? 68
Range 69
Variance 70
EXERCISES 72
Population Variance 73
Population Standard Deviation 75
EXERCISES 75
Sample Variance and Standard
Deviation 76
Software Solution 77
EXERCISES 78
Interpretation and Uses of the Standard Deviation 78
Chebyshev’s Theorem 78
The Empirical Rule 79
EXERCISES 80
Ethics and Reporting Results 81
Chapter Summary 81
Chapter Exercises 83
Data Analytics 86
Practice Test 86
4 Describing Data:
DISPLAYING AND EXPLORING DATA 88
Introduction 89
Dot Plots 89
EXERCISES 91
Measures of Position 92
Quartiles, Deciles, and Percentiles 92
EXERCISES 96
Box Plots 96
EXERCISES 99
Skewness 100
EXERCISES 103
Describing the Relationship between Two Variables 104
Contingency Tables 106
EXERCISES 108
Chapter Summary 109
Pronunciation Key 110
Chapter Exercises 110
Data Analytics 115
Practice Test 115
5 A Survey of Probability Concepts 117
Introduction 118
What is a Probability? 119
Approaches to Assigning Probabilities 121
Classical Probability 121
Empirical Probability 122
Subjective Probability 124
EXERCISES 125
Rules of Addition for Computing Probabilities 126
Special Rule of Addition 126
Complement Rule 128
The General Rule of Addition 129
EXERCISES 131
Rules of Multiplication to Calculate Probability 132
Special Rule of Multiplication 132
General Rule of Multiplication 133
Contingency Tables 135
Tree Diagrams 138
EXERCISES 140
Principles of Counting 142
The Multiplication Formula 142
The Permutation Formula 143
The Combination Formula 145
EXERCISES 147
Chapter Summary 147
Pronunciation Key 148
Chapter Exercises 148
Data Analytics 153
Practice Test 154
6 Discrete Probability Distributions 155
Introduction 156
What is a Probability Distribution? 156
Random Variables 158
Discrete Random Variable 159
Continuous Random Variable 160
The Mean, Variance, and Standard Deviation of a
Discrete Probability Distribution 160
Mean 160
Variance and Standard Deviation 160
EXERCISES 162
Binomial Probability Distribution 164
How is a Binomial Probability Computed? 165
Binomial Probability Tables 167
EXERCISES 170
Cumulative Binomial Probability Distributions 171
EXERCISES 172
Poisson Probability Distribution 173
EXERCISES 178
Chapter Summary 178
Chapter Exercises 179
Data Analytics 183
Practice Test 183
7 Continuous Probability
Distributions 184
Introduction 185
The Family of Uniform Probability Distributions 185
EXERCISES 188
The Family of Normal Probability Distributions 189
The Standard Normal Probability Distribution 192
Applications of the Standard Normal Distribution 193
The Empirical Rule 193
EXERCISES 195
Finding Areas under the Normal Curve 196
EXERCISES 199
EXERCISES 201
EXERCISES 204
Chapter Summary 204
Chapter Exercises 205
Data Analytics 208
Practice Test 209
8 Sampling Methods and the Central Limit Theorem 210
Introduction 211
Sampling Methods 211
Reasons to Sample 211
Simple Random Sampling 212
Systematic Random Sampling 215
Stratified Random Sampling 215
Cluster Sampling 216
EXERCISES 217
Sampling “Error” 219
Sampling Distribution of the Sample Mean 221
EXERCISES 224
The Central Limit Theorem 225
EXERCISES 231
Using the Sampling Distribution of the Sample Mean 232
EXERCISES 234
Chapter Summary 235
Pronunciation Key 236
Chapter Exercises 236
Data Analytics 241
Practice Test 241
9 Estimation and Confidence Intervals 242
Introduction 243
Point Estimate for a Population Mean 243
Confidence Intervals for a Population Mean 244
Population Standard Deviation, Known σ 244
A Computer Simulation 249
EXERCISES 251
Population Standard Deviation, σ Unknown 252
EXERCISES 259
A Confidence Interval for a Population Proportion 260
EXERCISES 263
Choosing an Appropriate Sample Size 263
Sample Size to Estimate a Population Mean 264
Sample Size to Estimate a Population Proportion 265
EXERCISES 267
Chapter Summary 267
Chapter Exercises 268
Data Analytics 272
Practice Test 273
10 One-Sample Tests of Hypothesis 274
Introduction 275
What is Hypothesis Testing? 275
Six-Step Procedure for Testing a Hypothesis 276
Step 1: State the Null Hypothesis (H0) and the Alternate Hypothesis (H1) 276
Step 2: Select a Level of Significance 277
Step 3: Select the Test Statistic 279
Step 4: Formulate the Decision Rule 279
Step 5: Make a Decision 280
Step 6: Interpret the Result 280
One-Tailed and Two-Tailed Hypothesis Tests 281
Hypothesis Testing for a Population Mean: Known
Population Standard Deviation 283
A Two-Tailed Test 283
A One-Tailed Test 286
p-Value in Hypothesis Testing 287
EXERCISES 289
Hypothesis Testing for a Population Mean: Population Standard Deviation Unknown 290
EXERCISES 295
A Statistical Software Solution 296
EXERCISES 297
Chapter Summary 299
Pronunciation Key 299
Chapter Exercises 300
Data Analytics 303
Practice Test 303
11 Two-Sample Tests of Hypothesis 305
Introduction 306
Two-Sample Tests of Hypothesis: Independent Samples 306
EXERCISES 311
Comparing Population Means with Unknown Population Standard Deviations 312
Two-Sample Pooled Test 312
EXERCISES 316
Two-Sample Tests of Hypothesis:
Dependent Samples 318
Comparing Dependent
and Independent Samples 321
EXERCISES 324
Chapter Summary 325
Pronunciation Key 326
Chapter Exercises 326
Data Analytics 332
Practice Test 332
12 Analysis of Variance 334
Introduction 335
Comparing Two Population Variances 335
The F Distribution 335
Testing a Hypothesis of Equal Population Variances 336
EXERCISES 339
ANOVA: Analysis of Variance 340
ANOVA Assumptions 340
The ANOVA Test 342
EXERCISES 349
Inferences about Pairs of Treatment Means 350
EXERCISES 352
Chapter Summary 354
Pronunciation Key 355
Chapter Exercises 355
Data Analytics 362
Practice Test 363
13 Correlation and
Linear Regression 365
Introduction 366
What is Correlation Analysis? 366
The Correlation Coefficient 369
EXERCISES 374
Testing the Significance of the Correlation Coefficient 376
EXERCISES 379
Regression Analysis 380
Least Squares Principle 380
Drawing the Regression Line 383
EXERCISES 386
Testing the Significance of the Slope 388
EXERCISES 390
Evaluating a Regression Equation’s Ability to Predict 391
The Standard Error of Estimate 391
The Coefficient of Determination 392
EXERCISES 393
Relationships among the Correlation Coefficient, the Coefficient of Determination, and the Standard
Error of Estimate 393
EXERCISES 395
Interval Estimates of Prediction 396
Assumptions Underlying Linear Regression 396
Constructing Confidence and Prediction Intervals 397
EXERCISES 400
Transforming Data 400
EXERCISES 403
Chapter Summary 404
Pronunciation Key 406
Chapter Exercises 406
Data Analytics 415
Practice Test 416
14 Multiple Regression
Analysis 418
Introduction 419
Multiple Regression Analysis 419
EXERCISES 423
Evaluating a Multiple Regression Equation 425
The ANOVA Table 425
Multiple Standard Error of Estimate 426
Coefficient of Multiple Determination 427
Adjusted Coefficient of Determination 428
EXERCISES 429
Inferences in Multiple Linear Regression 429
Global Test: Testing the Multiple Regression Model 429
Evaluating Individual Regression Coefficients 432
EXERCISES 435
Evaluating the Assumptions of Multiple Regression 436
Linear Relationship 437
Variation in Residuals Same for Large and Small ŷ Values 438
Distribution of Residuals 439
Multicollinearity 439
Independent Observations 441
Qualitative Independent Variables 442
Stepwise Regression 445
EXERCISES 447
Review of Multiple Regression 448
Chapter Summary 454
Pronunciation Key 455
Chapter Exercises 456
Data Analytics 466
Practice Test 467
15 Nonparametric Methods:
NOMINAL-LEVEL HYPOTHESIS TESTS 469
Introduction 470
Test a Hypothesis of a Population Proportion 470
EXERCISES 473
Two-Sample Tests about Proportions 474
EXERCISES 478
Goodness-of-Fit Tests: Comparing Observed and
Expected Frequency Distributions 479
Hypothesis Test of Equal Expected Frequencies 479
EXERCISES 484
Hypothesis Test of Unequal Expected
Frequencies 486
Limitations of Chi-Square 487
EXERCISES 489
Contingency Table Analysis 490
EXERCISES 493
Chapter Summary 494
Pronunciation Key 495
Chapter Exercises 495
Data Analytics 500
Practice Test 501
APPENDIXES 503
Appendix A: Data Sets 504
Appendix B: Tables 513
Appendix C: Software Commands 526
Appendix D: Answers to Odd-Numbered
Chapter Exercises 534
Solutions to Practice Tests 566
Appendix E: Answers to Self-Review 570
Glossary 578
Index 581
Key Formulas
Student’s t Distribution
Areas under the Normal Curve