Essentials Of Business Statistics: Communicating With numbers

Cover......Page 1
Essentials of Business Statistics......Page 2
Dedication......Page 6
ABOUT THE AUTHORS......Page 7
ACKNOWLEDGMENTS......Page 23
BRIEF CONTENTS......Page 27
CONTENTS......Page 28
Chapter 1: Statistics and Data......Page 33
1.1 The Relevance of Statistics......Page 35
1.2 What is Statistics?......Page 36
Cross-Sectional and Time Series Data......Page 37
Structured and Unstructured Data......Page 38
Data on the Web......Page 39
1.3 Variables and Scales of Measurement......Page 41
The Nominal Scale......Page 42
The Ordinal Scale......Page 43
The Interval Scale......Page 44
The Ratio Scale......Page 45
Synopsis of Introductory Case......Page 46
Conceptual Review......Page 47
Chapter 2: Tabular and Graphical Methods......Page 49
2.1 Summarizing Qualitative Data......Page 51
Pie Charts and Bar Charts......Page 52
A Pie Chart......Page 55
A Bar Chart......Page 56
2.2 Summarizing Quantitative Data......Page 58
Guidelines for Constructing a Frequency Distribution......Page 59
Histograms, Polygons, and Ogives......Page 63
A Histogram Constructed from Raw Data......Page 67
A Histogram Constructed from a Frequency Distribution......Page 68
An Ogive......Page 69
2.3 Stem-and-Leaf Diagrams......Page 73
2.4 Scatterplots......Page 75
Using Excel to Construct a Scatterplot......Page 77
Writing with Statistics......Page 78
Conceptual Review......Page 80
Exercises......Page 81
Case Studies......Page 84
Appendix 2.1 Guidelines for Other Software Packages......Page 86
Chapter 3: Numerical Descriptive Measures......Page 91
The Mean......Page 93
The Median......Page 95
The Mode......Page 96
The Weighted Mean......Page 97
Using Excel’s Function Option......Page 98
Using Excel’s Data Analysis Toolpak Option......Page 99
Note on Symmetry......Page 100
3.2 Percentiles and Boxplots......Page 102
Calculating the pth Percentile......Page 103
Constructing and Interpreting a Boxplot......Page 104
Range......Page 107
The Mean Absolute Deviation......Page 108
The Variance and the Standard Deviation......Page 109
The Coefficient of Variation......Page 110
Using Excel’s Data Analysis Toolpak Option......Page 111
3.4 Mean-Variance Analysis and the Sharpe Ratio......Page 112
Synopsis of Introductory Case......Page 114
3.5 Analysis of Relative Location......Page 115
The Empirical Rule......Page 116
z-Scores......Page 117
3.6 Summarizing Grouped Data......Page 120
3.7 Measures of Association......Page 123
Using Excel to Calculate Measures of Association......Page 125
Writing with Statistics......Page 126
Conceptual Review......Page 128
Exercises......Page 129
Case Studies......Page 132
Appendix 3.1: Guidelines for Other Software Packages......Page 133
Chapter 4: Introduction to Probability......Page 135
4.1 Fundamental Probability Concepts......Page 137
Events......Page 138
Assigning Probabilities......Page 140
The Complement Rule......Page 144
The Addition Rule......Page 145
The Addition Rule for Mutually Exclusive Events......Page 146
Conditional Probability......Page 147
Independent and Dependent Events......Page 149
The Multiplication Rule for Independent Events......Page 150
4.3 Contingency Tables and Probabilities......Page 154
Synopsis of Introductory Case......Page 157
The Total Probability Rule......Page 159
Bayes’ Theorem......Page 162
Writing With Statistics......Page 166
Conceptual Review......Page 168
Exercises......Page 169
Case Studies......Page 173
Chapter 5: Discrete Probability Distributions......Page 175
5.1 Random Variables and Discrete Probability Distributions......Page 177
The Discrete Probability Distribution......Page 178
5.2 Expected Value, Variance, and Standard Deviation......Page 182
Variance and Standard Deviation......Page 183
Risk Neutrality and Risk Aversion......Page 184
5.3 The Binomial Distribution......Page 187
Using Excel to Obtain Binomial Probabilities......Page 192
5.4 The Poisson Distribution......Page 195
Using Excel to Obtain Poisson Probabilities......Page 198
5.5 The Hypergeometric Distribution......Page 200
Using Excel to Obtain Hypergeometric Probabilities......Page 202
Writing with Statistics......Page 204
Conceptual Review......Page 206
Exercises......Page 207
Case Studies......Page 209
Appendix 5.1: Guidelines for Other Software Packages......Page 210
Chapter 6: Continuous Probability Distributions......Page 213
6.1 Continuous Random Variables and the Uniform Distribution......Page 215
The Continuous Uniform Distribution......Page 216
6.2 The Normal Distribution......Page 219
Characteristics of the Normal Distribution......Page 220
The Standard Normal Distribution......Page 221
Finding a Probability for a Given z Value......Page 222
Finding a z Value for a Given Probability......Page 224
The Transformation of Normal Random Variables......Page 226
Using Excel for the Normal Distribution......Page 230
6.3 The Exponential Distribution......Page 235
Using Excel for the Exponential Distribution......Page 238
Writing with Statistics......Page 240
Conceptual Review......Page 241
Exercises......Page 242
Case Studies......Page 245
Appendix 6.1: Guidelines for Other Software Packages......Page 246
Chapter 7: Sampling and Sampling Distributions......Page 249
Classic Case of a “Bad” Sample: The Literary Digest Debacle of 1936......Page 251
Trump’s Stunning Victory in 2016......Page 252
Sampling Methods......Page 253
Using Excel to Generate a Simple Random Sample......Page 255
7.2 The Sampling Distribution of the Sample Mean......Page 256
The Expected Value and the Standard Error of the Sample Mean......Page 257
Sampling from a Normal Population......Page 258
The Central Limit Theorem......Page 259
The Expected Value and the Standard Error of the Sample Proportion......Page 263
Synopsis of Introductory Case......Page 267
7.4 The Finite Population Correction Factor......Page 268
7.5 Statistical Quality Control......Page 271
Control Charts......Page 272
Using Excel to Create a Control Chart......Page 275
Writing with Statistics......Page 278
Conceptual Review......Page 279
Exercises......Page 281
Case Studies......Page 283
Appendix 7.1: Derivation of the Mean and the Variance for X and P......Page 284
Appendix 7.2: Properties of Point Estimators......Page 285
Appendix 7.3: Guidelines for Other Software Packages......Page 286
Chapter 8: Interval Estimation......Page 289
8.1 Confidence Interval for the Population Mean when σ is Known......Page 291
Constructing a Confidence Interval for μ When σ Is Known......Page 292
The Width of a Confidence Interval......Page 294
Using Excel to Construct a Confidence Interval for μ When σ Is Known......Page 296
Summary of the tdf Distribution......Page 299
Locating tdf Values and Probabilities......Page 300
Constructing a Confidence Interval for   When   Is Unknown......Page 301
Using Excel to Construct a Confidence Interval for   When   Is Unknown......Page 302
8.3 Confidence Interval for the Population Proportion......Page 306
8.4 Selecting the Required Sample Size......Page 309
Selecting n to Estimate......Page 310
Selecting n to Estimate p......Page 311
Synopsis of Introductory Case......Page 312
Writing with Statistics......Page 313
Conceptual Review......Page 315
Exercises......Page 316
Case Studies......Page 319
Appendix 8.1: Guidelines for Other Software Packages......Page 321
Chapter 9: Hypothesis Testing......Page 323
The Decision to “Reject” or “Not Reject” the Null Hypothesis......Page 325
Defining the Null and the Alternative Hypotheses......Page 326
Type I and Type II Errors......Page 328
The p-Value Approach......Page 331
Confidence Intervals and Two-Tailed Hypothesis Tests......Page 335
Using Excel to Test   When   Is Known......Page 336
One Last Remark......Page 337
9.3 Hypothesis Test for the Population Mean When σ is Unknown......Page 339
Using Excel to Test μ When σ is Unknown......Page 340
Synopsis of Introductory Case......Page 341
9.4 Hypothesis Test for the Population Proportion......Page 344
Writing with Statistics......Page 348
Conceptual Review......Page 349
Exercises......Page 351
Case Studies......Page 353
Appendix 9.1: The Critical Value Approach......Page 355
Appendix 9.2: Guidelines for Other Software Packages......Page 357
Chapter 10: Comparisons Involving Means......Page 359
Confidence Interval for μ1 − μ2......Page 361
Hypothesis Test for μ1 − μ2......Page 363
Using Excel for Testing Hypotheses about μ1 − μ2......Page 365
10.2 Inference Concerning Mean Differences......Page 371
Confidence Interval for μD......Page 372
Hypothesis Test for μD......Page 373
Using Excel for Testing Hypotheses about μD......Page 375
Synopsis of Introductory Case......Page 376
Finding F (df1 ,df2 ) Values and Probabilities......Page 380
One-Way ANOVA Test......Page 381
Between-Treatments Estimate of σ2: MSTR......Page 383
Within-Treatments Estimate of σ2: MSE......Page 384
Using Excel to Construct a One-Way ANOVA Table......Page 386
Writing with Statistics......Page 390
Conceptual Review......Page 391
Exercises......Page 393
Case Studies......Page 397
Appendix 10.1: Guidelines for Other Software Packages......Page 398
Chapter 11: Comparisons Involving Proportions......Page 401
Confidence Interval for p1 − p2......Page 403
Hypothesis Test for p1 − p2......Page 404
The X2 Distribution......Page 409
Finding  χd2f Values and Probabilities......Page 410
11.3 Chi-Square Test For Independence......Page 416
Synopsis of Introductory Case......Page 420
Writing with Statistics......Page 423
Conceptual Review......Page 424
Exercises......Page 425
Case Studies......Page 429
Appendix 11.1: Guidelines for Other Software Packages......Page 430
Chapter 12: Basics of Regression Analysis......Page 433
12.1 The Simple Linear Regression Model......Page 435
Determining the Sample Regression Equation......Page 437
Estimating a Simple Linear Regression Model......Page 439
12.2 The Multiple Linear Regression Model......Page 442
Using Excel to Estimate a Multiple Linear Regression Model......Page 444
The Standard Error of the Estimate......Page 447
The Coefficient of Determination, R2......Page 448
The Adjusted R2......Page 450
Tests of Individual Significance......Page 453
A Test for a Nonzero Slope Coefficient......Page 456
Test of Joint Significance......Page 458
Synopsis of Introductory Case......Page 460
12.5 Model Assumptions and Common Violations......Page 464
Detection......Page 466
Common Violation 2: Multicollinearity......Page 467
Detection......Page 468
Detection......Page 469
Remedy......Page 470
Detection......Page 471
Summary......Page 472
Using Excel to Construct Residual Plots......Page 473
Writing with Statistics......Page 475
Conceptual Review......Page 477
Additional Exercises and Case Studies......Page 479
Case Studies......Page 482
Appendix 12.1: Guidelines for Other Software Packages......Page 484
Chapter 13: More on Regression Analysis......Page 487
A Qualitative Explanatory Variable with Two Categories......Page 489
A Qualitative Explanatory Variable with Multiple Categories......Page 492
13.2 Interactions with Dummy Variables......Page 498
Synopsis of Introductory Case......Page 502
Quadratic Regression Models......Page 504
The Log-Log Model......Page 509
The Logarithmic Model......Page 510
The Exponential Model......Page 511
The Linear and the Exponential Trend......Page 518
Polynomial Trends......Page 521
Seasonal Dummy Variables......Page 526
Writing with Statistics......Page 530
Conceptual Review......Page 532
Additional Exercises and Case Studies......Page 534
Case Studies......Page 538
Appendix A Tables......Page 541
Appendix B Answers to Selected Even-Numbered Exercises......Page 551
Glossary......Page 568
INDEX......Page 576