The practice of business statistics: using data for decisions
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
New York, NY
Freeman
2009
|
| Ausgabe: | 2. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | getr. Zählung Ill., graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 9780716788256 142922150x 071678825X 9781429221504 |
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MARC
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| 245 | 1 | 0 | |a The practice of business statistics |b using data for decisions |c David S. Moore ... |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a New York, NY |b Freeman |c 2009 | |
| 300 | |a getr. Zählung |b Ill., graph. Darst. |e 1 CD-ROM (12 cm) | ||
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| 650 | 4 | |a Statistik | |
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Datensatz im Suchindex
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| adam_text |
BRIEF TABLE OF CONTENTS
PART I Data 1
Chapter 1 Examining Distributions 3
Chapter 2 Examining Relationships 93
Chapter 3 Producing Data 175
PART II Probability and Inference 241
Chapter 4 Probability and Sampling Distributions 243
Chapter 5 Probability Theory 311
Chapter 6 Introduction to Inference 359
Chapter 7 Inference for Distributions 423
Chapter 8 Inference for Proportions 493
PART III Topics in Inference 533
Chapter 9 Inference for Two-Way Tables 535
Chapter 10 Inference for Regression 569
Chapter 11 Multiple Regression 617
Chapter 12 Statistics for Quality: Control and Capability 685
Chapter 13 Time Series Forecasting 749
Chapter 14 One-Way Analysis of Variance 791
The Core book includes Chapters 1-14. Chapters 15-18 are individual optional
Companion Chapters.
PART IV Optional Companion Chapters
Chapter 15 Two-Way Analysis of Variance
Chapter 16 Nonparametric Tests
Chapter 17 Logistic Regression
Chapter 18 Bootstrap Methods and Permutation Tests
TABLE OF CONTENTS
To Instructors: About This Book xxiii
Media and Supplements xxxi
To Students: What Is Statistics? xxxv
Index of Cases xxxviii
Index of Data Tables xl
Beyond the Basics xliii
About the Authors xliv
PARTI Data 1
CHAPTER 1 Examining Distributions 3
Introduction 4
1.1 Displaying Distributions with Graphs 5
Categorical variables: bar graphs and pie charts 6
Quantitative variables: histograms 9
Case 1.1 State Unemployment Rates 9
Interpreting histograms 13
Quantitative variables: stemplots 17
Time plots 18
Section 1.1 Summary 21
Section 1.1 Exercises 22
1.2 Describing Distributions with Numbers 30
Case 1.2 Earnings of Hourly Bank Workers 30
Measuring center: the mean 30
Measuring center: the median 32
Comparing the mean and the median 33
Measuring spread: the quartiles 35
The five-number summary and boxplots 36
Measuring spread: the standard deviation 40
Choosing measures of center and spread 42
Section 1.2 Summary 44
Section 1.2 Exercises 45
1.3 The Normal Distributions 50
Density curves 50
The median and mean of a density curve 52
Normal distributions 55
The 68-95-99.7 rule 56
viii TABLE OF CONTENTS
The standard Normal distribution 58
Normal distribution calculations 59
Finding a value when given a proportion 64
Assessing the Normality of data 65
Beyond the basics: density estimation 69
Section 1.3 Summary 70
Section 1.3 Exercises 71
Statistics in Summary 74
Chapter 1 Review Exercises 76
Chapter 1 Case Study Exercises 81
Chapter 1 Appendix 82
CHAPTER 2 Examining Relationships 93
Introduction 94
2.1 Scatterplots 96
Case 2.1 Sales at a Retail Shop 96
Interpreting scatterplots 98
Adding categorical variables to scatterplots 101
Section 2.1 Summary 103
Section 2.1 Exercises 104
2.2 Correlation 110
The correlation r 111
Facts about correlation 112
Section 2.2 Summary 115
Section 2.2 Exercises 115
2.3 Least-Squares Regression 118
The least-squares regression line 119
Facts about least-squares regression 123
Residuals 126
Influential observations 128
Beyond the basics: scatterplot smoothers 131
Section 2.3 Summary 132
Section 2.3 Exercises 133
2.4 Cautions about Correlation
and Regression 140
Beware extrapolation 140
Beware correlations based on averaged data 141
Beware the lurking variable 141
Association is not causation 143
Beyond the basics: data mining 146
Section 2.4 Summary 146
Section 2.4 Exercises 147
TABLE OF CONTENTS i
2.5 Relations in Categorical Data 150
Case 2.2 Marital Status and Job Level 151
Marginal distributions 151
Describing relationships 153
Conditional distributions 154
Simpson's paradox 156
Section 2.5 Summary 158
Section 2.5 Exercises 158
Statistics in Summary 161
Chapter 2 Review Exercises 163
Chapter 2 Case Study Exercises 171
Chapter 2 Appendix 172
CHAPTER 3 Producing Data 175
Introduction 176
Observation and experiment 176
3.1 Designing Samples 178
Simple random samples 180
Stratified samples 184
Multistage samples 185
Cautions about sample surveys 186
Beyond the basics: capture-recapture sampling 189
Section 3.1 Summary 190
Section 3.1 Exercises 190
3.2 Designing Experiments 194
Comparative experiments 196
Randomized comparative experiments 197
Completely randomized designs 198
The logic of randomized comparative experiments 200
Cautions about experimentation 201
Matched pairs designs 203
Block designs 203
Section 3.2 Summary 206
Section 3.2 Exercises 206
3.3 Toward Statistical Inference 210
Case 3.1 Is Clothes Shopping Frustrating? 210
Sampling variability, sampling distributions 211
Bias and variability 216
Sampling from large populations 219
Why randomize? 219
Section 3.3 Summary 220
Section 3.3 Exercises 220
TABLE OF CONTENTS
3.4 Commentary: Data Ethics 224
Institutional review boards 225
Informed consent 226
Confidentiality 227
Clinical trials 227
Behavioral and social science experiments 229
Section 3.4 Summary 230
Section 3.4 Exercises 230
Statistics in Summary 233
Chapter 3 Review Exercises 234
Chapter 3 Case Study Exercises 238
Chapter 3 Appendix 239
PART II Probability andlnference 241
CHAPTER 4 Probabilityand Sampling Distributions 243
Introduction 244
4.1 Randomness 244
The idea of probability 244
Thinking about randomness 246
Section 4.1 Summary 247
Section 4.1 Exercises 247
4.2 Probability Models 249
Case 4.1 Uncovering Fraud by Digital Analysis 249
Probability rules 251
Assigning probabilities: finite number of outcomes 254
Assigning probabilities: intervals of outcomes 257
Normal probability models 259
Section 4.2 Summary 260
Section 4.2 Exercises 261
4.3 Random Variables 264
Probability distributions 265
The mean of a random variable 271
Rules for means 274
Case 4.2 Portfolio Analysis 274
The variance of a random variable 278
Rules for variances 280
Section 4.3 Summary 284
Section 4.3 Exercises 286
4.4 The Sampling Distribution of a Sample Mean 290
Statistical estimation and the law of large numbers 291
Thinking about the law of large numbers 293
Beyond the basics: more laws of large numbers 294
TABLE OF CONTENTS xi
Sampling distributions 296
The mean and the standard deviation of x 296
The central limit theorem 298
Section 4.4 Summary 301
Section 4.4 Exercises 302
Statistics in Summary 304
Chapter 4 Review Exercises 306
Chapter 4 Case Study Exercises 310
CHAPTER 5 Probability Theory 311
Introduction 312
5.1 General Probability Rules 312
Independence and the multiplication rule 312
Applying the multiplication rule 315
The general addition rule 317
Section 5.1 Summary 319
Section 5.1 Exercises 319
5.2 The Binomial Distributions 322
The binomial setting 322
Case 5.1 Inspecting a Supplier's Products 323
Binomial probabilities 324
Finding binomial probabilities: tables 326
Binomial mean and standard deviation 328
The Normal approximation to binomial distributions 330
Section 5.2 Summary 332
Section 5.2 Exercises 333
5.3 The Poisson Distributions 335
The Poisson setting 336
The Poisson model 338
Beyond the basics: more distribution
approximations 339
Section 5.3 Summary 340
Section 5.3 Exercises 340
5.4 Conditional Probability 342
Conditional probability and independence 345
Tree diagrams and Bayes's rule 347
Section 5.4 Summary 350
Section 5.4 Exercises 350
Statistics in Summary 352
Chapter 5 Review Exercises 353
Chapter 5 Case Study Exercises 357
Chapter 5 Appendix 357
TABLE OF CONTENTS
CHAPTER 6 Introduction to Inference 359
Introduction 360
6.1 Estimating with Confidence 362
Case 6.1 Community Banks 362
Statistical confidence 363
Confidence intervals 364
Confidence interval for a population mean 366
How confidence intervals behave 368
Choosing the sample size 369
Some cautions 371
Beyond the basics: the bootstrap 372
Section 6.1 Summary 373
Section 6.1 Exercises 374
6.2 Tests of Significance 377
The reasoning of significance tests 377
Stating hypotheses 378
Test statistics 381
P-values 382
Statistical significance 384
Tests for a population mean 385
Two-sided significance tests and confidence intervals 389
P-values versus fixed a 391
Section 6.2 Summary 393
Section 6.2 Exercises 394
6.3 Using Significance Tests 398
How small a P is convincing? 398
Statistical significance and practical significance 399
Statistical inference is not valid for all sets of data 400
Beware of searching for significance 400
Section 6.3 Summary 401
Section 6.3 Exercises 402
6.4 Power and Inference as a Decision 403
The power of a statistical test 403
Increasing the power 406
Inference as decision 408
Two types of error 408
Error probabilities 409
The common practice of testing hypotheses 411
Section 6.4 Summary 412
Section 6.4 Exercises 412
Statistics in Summary 414
Chapter 6 Review Exercises 415
Chapter 6 Case Study Exercises 418
Chapter 6 Appendix 419
TABLE OF CONTENTS xiii
CHAPTER 7 Inference for Distributions 423
Introduction 424
7.1 Inference for the Mean of a Population 424
The; distributions 424
The one-sample t confidence interval 426
Case 7.1 Producing a Fortified Food Product 427
The one-sample t test 428
Using software 431
Matched pairs t procedures 434
Robustness of the t procedures 436
The power of the / test 438
Inference for non-Normal populations 440
Section 7.1 Summary 442
Section 7.1 Exercises 443
7.2 Comparing Two Means 449
The two-sample z statistic 450
The two-sample t procedures 451
The two-sample t significance test 452
The two-sample t confidence interval 454
Robustness of the two-sample procedures 456
Inference for small samples 457
Satterthwaite approximation for the degrees of freedom 460
The pooled two-sample t procedures 461
Case 7.2 Healthy Companies versus Failed Companies 462
Section 7.2 Summary 466
Section 7.2 Exercises 467
7.3 Optional Topics in Comparing Distributions 472
Inference for population spread 473
The F test for equality of spread 473
The power of the two-sample t test 476
Section 7.3 Summary 478
Section 7.3 Exercises 478
Statistics in Summary 480
Chapter 7 Review Exercises 481
Chapter 7 Case Study Exercises 486
Chapter 7 Appendix 487
CHAPTER 8 Inference for Proportions 493
Introduction 494
8.1 Inference for a Single Proportion 494
Case 8.1 Work Stress and Personal Life 494
Large-sample confidence interval for a single proportion 495
Plus four confidence interval for a single proportion 498
TABLE OF CONTENTS
Significance test for a single proportion 498
Choosing a sample size 501
Case 8.2 Marketing Christmas Trees 503
Section 8.1 Summary 505
Section 8.1 Exercises 506
8.2 Comparing Two Proportions 510
Large-sample confidence intervals for a difference
in proportions 512
Case 8.3 "No Sweat" Garment Labels 512
Plus four confidence intervals for a difference
in proportions 514
Significance tests 515
Beyond the basics: relative risk 518
Section 8.2 Summary 520
Section 8.2 Exercises 521
Statistics in Summary 524
Chapter 8 Review Exercises 525
Chapter 8 Case Study Exercises 530
Chapter 8 Appendix 530
PART III Topics in Inference 533
CHAPTER 9 Inference for Two-Way Tables 535
9.1 Analysis of Two-Way Tables 536
Two-way tables 536
Case 9.1 Exclusive Territories and the Success of
New Franchise Chains 537
Describing relations in two-way tables 538
The hypothesis: no association 541
Expected cell counts 541
The chi-square test 542
The chi-square test and the z test 545
Beyond the basics: meta-analysis 546
Section 9.1 Summary 547
9.2 Formulas and Models for Two-Way Tables 548
Case 9.2 Background Music and Consumer
Behavior 548
Conditional distributions 549
Expected cell counts 551
The X2 statistic and its P-value 552
Models for two-way tables 553
Concluding remarks 555
Section 9.2 Summary 555
TABLE OF CONTENTS xv
Statistics in Summary 555
Chapter 9 Review Exercises 556
Chapter 9 Case Study Exercises 565
Chapter 9 Appendix 567
CHAPTER 10 Inference for Regression 569
Introduction 570
10.1 Inference about the Regression Model 570
Statistical model for simple linear regression 571
From data analysis to inference 571
Cose 10.1 Do Wages Rise with Experience? 572
Estimating the regression parameters 577
Conditions for regression inference 581
Confidence intervals and significance tests 582
The word "regression" 585
Inference about correlation 587
Section 10.1 Summary 589
Section 10.1 Exercises 589
10.2 Using the Regression Line 594
Beyond the basics: nonlinear regression 599
Section 10.2 Summary 599
Section 10.2 Exercises 600
10.3 Some Details of Regression Inference 601
Standard errors 602
Analysis of variance for regression 604
Section 10.3 Summary 608
Section 10.3 Exercises 608
Statistics in Summary 609
Chapter 10 Review Exercises 610
Chapter 10 Case Study Exercises 613
Chapter 10 Appendix 615
CHAPTER 11 Multiple Regression 617
Introduction 618
Case 11.1 Assets, Sales, and Profits 620
11.1 Data Analysis for Multiple Regression 620
Data for multiple regression 620
Preliminary data analysis for multiple regression 622
Estimating the multiple regression coefficients 626
Regression residuals 627
The regression standard error 632
xvi TABLE OF CONTENTS
Section 11.1 Summary 633
Section 11.1 Exercises 634
11.2 Inference for Multiple Regression 636
Multiple linear regression model 637
Case 11.2 Predicting College GPA 637
Estimating the parameters of the model 638
Inference about the regression coefficients 639
Inference about prediction 643
ANOVA table for multiple regression 644
Squared multiple correlation R2 646
Inference for a collection of regression coefficients 647
Section 11.2 Summary 649
Section 11.2 Exercises 650
11.3 Multiple Regression Model Building 654
Case 11.3 Prices of Homes 654
Models for curved relationships 657
Models with categorical explanatory variables 659
More elaborate models 663
Variable selection methods 666
Beyond the basics: multiple logistic regression 669
Section 11.3 Summary 670
Section 11.3 Exercises 671
Statistics in Summary 672
Chapter 11 Review Exercises 673
Chapter 11 Case Study Exercises 681
Chapter 11 Appendix 682
CHAPTER 12 Statistics for Quality: Control
and Capability 685
Introduction 686
Processes 687
Systematic approach to process improvement 688
Process improvement toolkit 689
Case 12.1 Hot Forging 690
12.1 Statistical Process Control 693
x charts for process monitoring 694
Case 12.2 Manufacturing Computer Monitors 696
^ charts for process monitoring 701
Section 12.1 Summary 707
Section 12.1 Exercises 707
12.2 Using Control Charts 709
x and R charts 709
Additional out-of-control signals 710
TABLE OF CONTENTS xvii
Setting up control charts 712
Case 12.3 Viscosity of an Elastomer 712
Comments on statistical control 717
Don't confuse control with capability! 720
Section 12.2 Summary 722
Section 12.2 Exercises 723
12.3 Process Capability Indexes 725
The capability indexes Cp and CPk 728
Cautions about capability indexes 731
Section 12.3 Summary 733
Section 12.3 Exercises 733
12.4 Control Charts for Sample
Proportions 736
Control limits for p charts 737
Case 12.4 Reducing Absenteeism 738
Section 12.4 Summary 741
Section 12.4 Exercises 741
Statistics in Summary 742
Chapter 12 Review Exercises 743
Chapter 12 Appendix 745
CHAPTER 13 Time Series Forecasting. 749
Introduction 750
13.1 Trends and Seasons 752
Identifying trends 753
Case 13.1 Selling DVD Players 754
Seasonal patterns 756
Looking for autocorrelation 762
Section 13.1 Summary 765
Section 13.1 Exercises 765
13.2 Time Series Models 768
Autoregressive models 768
Moving average models 773
Exponential smoothing models 776
Beyond the basics: spline fits 779
Section 13.2 Summary 780
Section 13.2 Exercises 781
Statistics in Summary 783
Chapter 13 Review Exercises 784
Chapter 13 Appendix 786
TABLE OF CONTENTS
CHAPTER 14 .?ne-Way Analysis of Variance 791
Introduction 792
14.1 One-Way Analysis of Variance 792
The ANOVA setting: comparing means 792
The two-sample t statistic 794
An overview of ANOVA 795
The ANOVA model 797
Estimates of population parameters 799
Testing hypotheses in one-way ANOVA 801
Case 14.1 A New Educational Product 802
The ANOVA table 805
The F test 808
Using software 810
Section 14.1 Summary 812
14.2 Comparing Group Means 812
Contrasts 813
Case 14.2 Evaluation of the New Product 813
Multiple comparisons 819
Simultaneous confidence intervals 824
Section 14.2 Summary 825
14.3 The Power of the ANOVA Test 825
Section 14.3 Summary 828
Statistics in Summary 828
Chapter 14 Review Exercises 829
Chapter 14 Case Study Exercises 841
Chapter 14 Appendix 841
NOTES AND DATA SOURCES N-1
DATA APPENDIX A-l
TABLES T-l
SOLUTIONS TO ODD-NUMBERED EXERCISES S-1
INDEX 1-1
PART IV Optional Individual Companion Chapters
CHAPTER 15 Jwo-Way Analysis of Variance
Introduction
15.1 The Two-Way ANOVA Model
Advantages of two-way ANOVA
The two-way ANOVA model
Main effects and interactions
Section 15.1 Summary
TABLE OF CONTENTS
15.2 Inference for Two-Way ANOVA
The ANOVA table for two-way ANOVA
Carrying out a two-way ANOVA
Case 15.1 Discounts and Expected Prices
Case 15.2 Expected Prices, Continued
Section 15.2 Summary
Statistics in Summary
Chapter 15 Review Exercises
Chapter 15 Case Study Exercises
CHAPTER 16 Nonparamerric Tests
Introduction
16.1 The Wilcoxon Rank Sum Test
Case 16.1 Earnings of Hourly Bank Workers
The rank transformation
The Wilcoxon rank sum test
The Normal approximation
What hypothesis does Wilcoxon test?
Ties
Case 16.2 Consumer Perceptions of Food Safety
Limitations of nonparametric tests
Section 16.1 Summary
16.2 The Wilcoxon Signed Rank Test
The Normal approximation
Ties
Section 16.2 Summary
16.3 The Kruskal-Wallis Test
Hypotheses and assumptions
The Kruskal-Wallis test
Section 16.3 Summary
Statistics in Summary
Chapter 16 Review Exercises
CHAPTER 17 Logistic Regression
Introduction
17.1 The Logistic Regression Model
Case 17.1 Binge Drinkers
Binomial distributions and odds
Model for logistic regression
Fitting and interpreting the logistic regression model
Section 17.1 Summary
xx TABLE OF CONTENTS
17.2 Inference for Logistic Regression
Examples of logistic regression analyses
Section 17.2 Summary
17.3 Multiple Logistic Regression
Section 17.3 Summary
Statistics in Summary
Chapter 17 Review Exercises
Chapter 17 Case Study Exercises
CHAPTER 18 Bootstrap Methods and Permutation Tests
18.1 Why Resampling?
Note on software
18.2 Introduction to Bootstrapping
Case 18.1 Telecommunication Repair Times
Procedure for bootstrapping
Using software
Why does bootstrapping work?
Sampling distributions and bootstrap distribution
Section 18.2 Summary
Section 18.2 Exercises
18.3 Bootstrap Distributions and Standard Errors
Case 18.2 Real Estate Sale Prices
Bootstrap distributions of other statistics
Bootstrap t confidence intervals
Bootstrapping to compare two groups
Beyond the basics: the bootstrap for a scatterplot smoother
Section 18.3 Summary
Section 18.3 Exercises
18.4 How Accurate Is a Bootstrap Distribution?
Bootstrapping small samples
Bootstrapping a sample median
Section 18.4 Summary
Section 18.4 Exercises
18.5 Bootstrap Confidence Intervals
Bootstrap percentiles as a check
Confidence intervals for the correlation
Case 18.3 Baseball Salaries and Performance
More accurate bootstrap confidence intervals
Bootstrap tilting and BCa intervals
How BCa and tilting intervals work
Section 18.5 Summary
Section 18.5 Exercises
TABLE OF CONTENTS
18.6 Significance Testing Using Permutation Tests
Using software
Permutation tests in practice
Permutation tests in other settings
Section 18.6 Summary
Section 18.6 Exercises
Statistics in Summary
Chapter 18 Review Exercises |
| adam_txt |
BRIEF TABLE OF CONTENTS
PART I Data 1
Chapter 1 Examining Distributions 3
Chapter 2 Examining Relationships 93
Chapter 3 Producing Data 175
PART II Probability and Inference 241
Chapter 4 Probability and Sampling Distributions 243
Chapter 5 Probability Theory 311
Chapter 6 Introduction to Inference 359
Chapter 7 Inference for Distributions 423
Chapter 8 Inference for Proportions 493
PART III Topics in Inference 533
Chapter 9 Inference for Two-Way Tables 535
Chapter 10 Inference for Regression 569
Chapter 11 Multiple Regression 617
Chapter 12 Statistics for Quality: Control and Capability 685
Chapter 13 Time Series Forecasting 749
Chapter 14 One-Way Analysis of Variance 791
The Core book includes Chapters 1-14. Chapters 15-18 are individual optional
Companion Chapters.
PART IV Optional Companion Chapters
Chapter 15 Two-Way Analysis of Variance
Chapter 16 Nonparametric Tests
Chapter 17 Logistic Regression
Chapter 18 Bootstrap Methods and Permutation Tests
TABLE OF CONTENTS
To Instructors: About This Book xxiii
Media and Supplements xxxi
To Students: What Is Statistics? xxxv
Index of Cases xxxviii
Index of Data Tables xl
Beyond the Basics xliii
About the Authors xliv
PARTI Data 1
CHAPTER 1 Examining Distributions 3
Introduction 4
1.1 Displaying Distributions with Graphs 5
Categorical variables: bar graphs and pie charts 6
Quantitative variables: histograms 9
Case 1.1 State Unemployment Rates 9
Interpreting histograms 13
Quantitative variables: stemplots 17
Time plots 18
Section 1.1 Summary 21
Section 1.1 Exercises 22
1.2 Describing Distributions with Numbers 30
Case 1.2 Earnings of Hourly Bank Workers 30
Measuring center: the mean 30
Measuring center: the median 32
Comparing the mean and the median 33
Measuring spread: the quartiles 35
The five-number summary and boxplots 36
Measuring spread: the standard deviation 40
Choosing measures of center and spread 42
Section 1.2 Summary 44
Section 1.2 Exercises 45
1.3 The Normal Distributions 50
Density curves 50
The median and mean of a density curve 52
Normal distributions 55
The 68-95-99.7 rule 56
viii TABLE OF CONTENTS
The standard Normal distribution 58
Normal distribution calculations 59
Finding a value when given a proportion 64
Assessing the Normality of data 65
Beyond the basics: density estimation 69
Section 1.3 Summary 70
Section 1.3 Exercises 71
Statistics in Summary 74
Chapter 1 Review Exercises 76
Chapter 1 Case Study Exercises 81
Chapter 1 Appendix 82
CHAPTER 2 Examining Relationships 93
Introduction 94
2.1 Scatterplots 96
Case 2.1 Sales at a Retail Shop 96
Interpreting scatterplots 98
Adding categorical variables to scatterplots 101
Section 2.1 Summary 103
Section 2.1 Exercises 104
2.2 Correlation 110
The correlation r 111
Facts about correlation 112
Section 2.2 Summary 115
Section 2.2 Exercises 115
2.3 Least-Squares Regression 118
The least-squares regression line 119
Facts about least-squares regression 123
Residuals 126
Influential observations 128
Beyond the basics: scatterplot smoothers 131
Section 2.3 Summary 132
Section 2.3 Exercises 133
2.4 Cautions about Correlation
and Regression 140
Beware extrapolation 140
Beware correlations based on averaged data 141
Beware the lurking variable 141
Association is not causation 143
Beyond the basics: data mining 146
Section 2.4 Summary 146
Section 2.4 Exercises 147
TABLE OF CONTENTS i
2.5 Relations in Categorical Data 150
Case 2.2 Marital Status and Job Level 151
Marginal distributions 151
Describing relationships 153
Conditional distributions 154
Simpson's paradox 156
Section 2.5 Summary 158
Section 2.5 Exercises 158
Statistics in Summary 161
Chapter 2 Review Exercises 163
Chapter 2 Case Study Exercises 171
Chapter 2 Appendix 172
CHAPTER 3 Producing Data 175
Introduction 176
Observation and experiment 176
3.1 Designing Samples 178
Simple random samples 180
Stratified samples 184
Multistage samples 185
Cautions about sample surveys 186
Beyond the basics: capture-recapture sampling 189
Section 3.1 Summary 190
Section 3.1 Exercises 190
3.2 Designing Experiments 194
Comparative experiments 196
Randomized comparative experiments 197
Completely randomized designs 198
The logic of randomized comparative experiments 200
Cautions about experimentation 201
Matched pairs designs 203
Block designs 203
Section 3.2 Summary 206
Section 3.2 Exercises 206
3.3 Toward Statistical Inference 210
Case 3.1 Is Clothes Shopping Frustrating? 210
Sampling variability, sampling distributions 211
Bias and variability 216
Sampling from large populations 219
Why randomize? 219
Section 3.3 Summary 220
Section 3.3 Exercises 220
TABLE OF CONTENTS
3.4 Commentary: Data Ethics 224
Institutional review boards 225
Informed consent 226
Confidentiality 227
Clinical trials 227
Behavioral and social science experiments 229
Section 3.4 Summary 230
Section 3.4 Exercises 230
Statistics in Summary 233
Chapter 3 Review Exercises 234
Chapter 3 Case Study Exercises 238
Chapter 3 Appendix 239
PART II Probability andlnference 241
CHAPTER 4 Probabilityand Sampling Distributions 243
Introduction 244
4.1 Randomness 244
The idea of probability 244
Thinking about randomness 246
Section 4.1 Summary 247
Section 4.1 Exercises 247
4.2 Probability Models 249
Case 4.1 Uncovering Fraud by Digital Analysis 249
Probability rules 251
Assigning probabilities: finite number of outcomes 254
Assigning probabilities: intervals of outcomes 257
Normal probability models 259
Section 4.2 Summary 260
Section 4.2 Exercises 261
4.3 Random Variables 264
Probability distributions 265
The mean of a random variable 271
Rules for means 274
Case 4.2 Portfolio Analysis 274
The variance of a random variable 278
Rules for variances 280
Section 4.3 Summary 284
Section 4.3 Exercises 286
4.4 The Sampling Distribution of a Sample Mean 290
Statistical estimation and the law of large numbers 291
Thinking about the law of large numbers 293
Beyond the basics: more laws of large numbers 294
TABLE OF CONTENTS xi
Sampling distributions 296
The mean and the standard deviation of x 296
The central limit theorem 298
Section 4.4 Summary 301
Section 4.4 Exercises 302
Statistics in Summary 304
Chapter 4 Review Exercises 306
Chapter 4 Case Study Exercises 310
CHAPTER 5 Probability Theory 311
Introduction 312
5.1 General Probability Rules 312
Independence and the multiplication rule 312
Applying the multiplication rule 315
The general addition rule 317
Section 5.1 Summary 319
Section 5.1 Exercises 319
5.2 The Binomial Distributions 322
The binomial setting 322
Case 5.1 Inspecting a Supplier's Products 323
Binomial probabilities 324
Finding binomial probabilities: tables 326
Binomial mean and standard deviation 328
The Normal approximation to binomial distributions 330
Section 5.2 Summary 332
Section 5.2 Exercises 333
5.3 The Poisson Distributions 335
The Poisson setting 336
The Poisson model 338
Beyond the basics: more distribution
approximations 339
Section 5.3 Summary 340
Section 5.3 Exercises 340
5.4 Conditional Probability 342
Conditional probability and independence 345
Tree diagrams and Bayes's rule 347
Section 5.4 Summary 350
Section 5.4 Exercises 350
Statistics in Summary 352
Chapter 5 Review Exercises 353
Chapter 5 Case Study Exercises 357
Chapter 5 Appendix 357
TABLE OF CONTENTS
CHAPTER 6 Introduction to Inference 359
Introduction 360
6.1 Estimating with Confidence 362
Case 6.1 Community Banks 362
Statistical confidence 363
Confidence intervals 364
Confidence interval for a population mean 366
How confidence intervals behave 368
Choosing the sample size 369
Some cautions 371
Beyond the basics: the bootstrap 372
Section 6.1 Summary 373
Section 6.1 Exercises 374
6.2 Tests of Significance 377
The reasoning of significance tests 377
Stating hypotheses 378
Test statistics 381
P-values 382
Statistical significance 384
Tests for a population mean 385
Two-sided significance tests and confidence intervals 389
P-values versus fixed a 391
Section 6.2 Summary 393
Section 6.2 Exercises 394
6.3 Using Significance Tests 398
How small a P is convincing? 398
Statistical significance and practical significance 399
Statistical inference is not valid for all sets of data 400
Beware of searching for significance 400
Section 6.3 Summary 401
Section 6.3 Exercises 402
6.4 Power and Inference as a Decision 403
The power of a statistical test 403
Increasing the power 406
Inference as decision 408
Two types of error 408
Error probabilities 409
The common practice of testing hypotheses 411
Section 6.4 Summary 412
Section 6.4 Exercises 412
Statistics in Summary 414
Chapter 6 Review Exercises 415
Chapter 6 Case Study Exercises 418
Chapter 6 Appendix 419
TABLE OF CONTENTS xiii
CHAPTER 7 Inference for Distributions 423
Introduction 424
7.1 Inference for the Mean of a Population 424
The; distributions 424
The one-sample t confidence interval 426
Case 7.1 Producing a Fortified Food Product 427
The one-sample t test 428
Using software 431
Matched pairs t procedures 434
Robustness of the t procedures 436
The power of the / test 438
Inference for non-Normal populations 440
Section 7.1 Summary 442
Section 7.1 Exercises 443
7.2 Comparing Two Means 449
The two-sample z statistic 450
The two-sample t procedures 451
The two-sample t significance test 452
The two-sample t confidence interval 454
Robustness of the two-sample procedures 456
Inference for small samples 457
Satterthwaite approximation for the degrees of freedom 460
The pooled two-sample t procedures 461
Case 7.2 Healthy Companies versus Failed Companies 462
Section 7.2 Summary 466
Section 7.2 Exercises 467
7.3 Optional Topics in Comparing Distributions 472
Inference for population spread 473
The F test for equality of spread 473
The power of the two-sample t test 476
Section 7.3 Summary 478
Section 7.3 Exercises 478
Statistics in Summary 480
Chapter 7 Review Exercises 481
Chapter 7 Case Study Exercises 486
Chapter 7 Appendix 487
CHAPTER 8 Inference for Proportions 493
Introduction 494
8.1 Inference for a Single Proportion 494
Case 8.1 Work Stress and Personal Life 494
Large-sample confidence interval for a single proportion 495
Plus four confidence interval for a single proportion 498
TABLE OF CONTENTS
Significance test for a single proportion 498
Choosing a sample size 501
Case 8.2 Marketing Christmas Trees 503
Section 8.1 Summary 505
Section 8.1 Exercises 506
8.2 Comparing Two Proportions 510
Large-sample confidence intervals for a difference
in proportions 512
Case 8.3 "No Sweat" Garment Labels 512
Plus four confidence intervals for a difference
in proportions 514
Significance tests 515
Beyond the basics: relative risk 518
Section 8.2 Summary 520
Section 8.2 Exercises 521
Statistics in Summary 524
Chapter 8 Review Exercises 525
Chapter 8 Case Study Exercises 530
Chapter 8 Appendix 530
PART III Topics in Inference 533
CHAPTER 9 Inference for Two-Way Tables 535
9.1 Analysis of Two-Way Tables 536
Two-way tables 536
Case 9.1 Exclusive Territories and the Success of
New Franchise Chains 537
Describing relations in two-way tables 538
The hypothesis: no association 541
Expected cell counts 541
The chi-square test 542
The chi-square test and the z test 545
Beyond the basics: meta-analysis 546
Section 9.1 Summary 547
9.2 Formulas and Models for Two-Way Tables 548
Case 9.2 Background Music and Consumer
Behavior 548
Conditional distributions 549
Expected cell counts 551
The X2 statistic and its P-value 552
Models for two-way tables 553
Concluding remarks 555
Section 9.2 Summary 555
TABLE OF CONTENTS xv
Statistics in Summary 555
Chapter 9 Review Exercises 556
Chapter 9 Case Study Exercises 565
Chapter 9 Appendix 567
CHAPTER 10 Inference for Regression 569
Introduction 570
10.1 Inference about the Regression Model 570
Statistical model for simple linear regression 571
From data analysis to inference 571
Cose 10.1 Do Wages Rise with Experience? 572
Estimating the regression parameters 577
Conditions for regression inference 581
Confidence intervals and significance tests 582
The word "regression" 585
Inference about correlation 587
Section 10.1 Summary 589
Section 10.1 Exercises 589
10.2 Using the Regression Line 594
Beyond the basics: nonlinear regression 599
Section 10.2 Summary 599
Section 10.2 Exercises 600
10.3 Some Details of Regression Inference 601
Standard errors 602
Analysis of variance for regression 604
Section 10.3 Summary 608
Section 10.3 Exercises 608
Statistics in Summary 609
Chapter 10 Review Exercises 610
Chapter 10 Case Study Exercises 613
Chapter 10 Appendix 615
CHAPTER 11 Multiple Regression 617
Introduction 618
Case 11.1 Assets, Sales, and Profits 620
11.1 Data Analysis for Multiple Regression 620
Data for multiple regression 620
Preliminary data analysis for multiple regression 622
Estimating the multiple regression coefficients 626
Regression residuals 627
The regression standard error 632
xvi TABLE OF CONTENTS
Section 11.1 Summary 633
Section 11.1 Exercises 634
11.2 Inference for Multiple Regression 636
Multiple linear regression model 637
Case 11.2 Predicting College GPA 637
Estimating the parameters of the model 638
Inference about the regression coefficients 639
Inference about prediction 643
ANOVA table for multiple regression 644
Squared multiple correlation R2 646
Inference for a collection of regression coefficients 647
Section 11.2 Summary 649
Section 11.2 Exercises 650
11.3 Multiple Regression Model Building 654
Case 11.3 Prices of Homes 654
Models for curved relationships 657
Models with categorical explanatory variables 659
More elaborate models 663
Variable selection methods 666
Beyond the basics: multiple logistic regression 669
Section 11.3 Summary 670
Section 11.3 Exercises 671
Statistics in Summary 672
Chapter 11 Review Exercises 673
Chapter 11 Case Study Exercises 681
Chapter 11 Appendix 682
CHAPTER 12 Statistics for Quality: Control
and Capability 685
Introduction 686
Processes 687
Systematic approach to process improvement 688
Process improvement toolkit 689
Case 12.1 Hot Forging 690
12.1 Statistical Process Control 693
x charts for process monitoring 694
Case 12.2 Manufacturing Computer Monitors 696
^ charts for process monitoring 701
Section 12.1 Summary 707
Section 12.1 Exercises 707
12.2 Using Control Charts 709
x and R charts 709
Additional out-of-control signals 710
TABLE OF CONTENTS xvii
Setting up control charts 712
Case 12.3 Viscosity of an Elastomer 712
Comments on statistical control 717
Don't confuse control with capability! 720
Section 12.2 Summary 722
Section 12.2 Exercises 723
12.3 Process Capability Indexes 725
The capability indexes Cp and CPk 728
Cautions about capability indexes 731
Section 12.3 Summary 733
Section 12.3 Exercises 733
12.4 Control Charts for Sample
Proportions 736
Control limits for p charts 737
Case 12.4 Reducing Absenteeism 738
Section 12.4 Summary 741
Section 12.4 Exercises 741
Statistics in Summary 742
Chapter 12 Review Exercises 743
Chapter 12 Appendix 745
CHAPTER 13 Time Series Forecasting. 749
Introduction 750
13.1 Trends and Seasons 752
Identifying trends 753
Case 13.1 Selling DVD Players 754
Seasonal patterns 756
Looking for autocorrelation 762
Section 13.1 Summary 765
Section 13.1 Exercises 765
13.2 Time Series Models 768
Autoregressive models 768
Moving average models 773
Exponential smoothing models 776
Beyond the basics: spline fits 779
Section 13.2 Summary 780
Section 13.2 Exercises 781
Statistics in Summary 783
Chapter 13 Review Exercises 784
Chapter 13 Appendix 786
TABLE OF CONTENTS
CHAPTER 14 .?ne-Way Analysis of Variance 791
Introduction 792
14.1 One-Way Analysis of Variance 792
The ANOVA setting: comparing means 792
The two-sample t statistic 794
An overview of ANOVA 795
The ANOVA model 797
Estimates of population parameters 799
Testing hypotheses in one-way ANOVA 801
Case 14.1 A New Educational Product 802
The ANOVA table 805
The F test 808
Using software 810
Section 14.1 Summary 812
14.2 Comparing Group Means 812
Contrasts 813
Case 14.2 Evaluation of the New Product 813
Multiple comparisons 819
Simultaneous confidence intervals 824
Section 14.2 Summary 825
14.3 The Power of the ANOVA Test 825
Section 14.3 Summary 828
Statistics in Summary 828
Chapter 14 Review Exercises 829
Chapter 14 Case Study Exercises 841
Chapter 14 Appendix 841
NOTES AND DATA SOURCES N-1
DATA APPENDIX A-l
TABLES T-l
SOLUTIONS TO ODD-NUMBERED EXERCISES S-1
INDEX 1-1
PART IV Optional Individual Companion Chapters
CHAPTER 15 Jwo-Way Analysis of Variance
Introduction
15.1 The Two-Way ANOVA Model
Advantages of two-way ANOVA
The two-way ANOVA model
Main effects and interactions
Section 15.1 Summary
TABLE OF CONTENTS
15.2 Inference for Two-Way ANOVA
The ANOVA table for two-way ANOVA
Carrying out a two-way ANOVA
Case 15.1 Discounts and Expected Prices
Case 15.2 Expected Prices, Continued
Section 15.2 Summary
Statistics in Summary
Chapter 15 Review Exercises
Chapter 15 Case Study Exercises
CHAPTER 16 Nonparamerric Tests
Introduction
16.1 The Wilcoxon Rank Sum Test
Case 16.1 Earnings of Hourly Bank Workers
The rank transformation
The Wilcoxon rank sum test
The Normal approximation
What hypothesis does Wilcoxon test?
Ties
Case 16.2 Consumer Perceptions of Food Safety
Limitations of nonparametric tests
Section 16.1 Summary
16.2 The Wilcoxon Signed Rank Test
The Normal approximation
Ties
Section 16.2 Summary
16.3 The Kruskal-Wallis Test
Hypotheses and assumptions
The Kruskal-Wallis test
Section 16.3 Summary
Statistics in Summary
Chapter 16 Review Exercises
CHAPTER 17 Logistic Regression
Introduction
17.1 The Logistic Regression Model
Case 17.1 Binge Drinkers
Binomial distributions and odds
Model for logistic regression
Fitting and interpreting the logistic regression model
Section 17.1 Summary
xx TABLE OF CONTENTS
17.2 Inference for Logistic Regression
Examples of logistic regression analyses
Section 17.2 Summary
17.3 Multiple Logistic Regression
Section 17.3 Summary
Statistics in Summary
Chapter 17 Review Exercises
Chapter 17 Case Study Exercises
CHAPTER 18 Bootstrap Methods and Permutation Tests
18.1 Why Resampling?
Note on software
18.2 Introduction to Bootstrapping
Case 18.1 Telecommunication Repair Times
Procedure for bootstrapping
Using software
Why does bootstrapping work?
Sampling distributions and bootstrap distribution
Section 18.2 Summary
Section 18.2 Exercises
18.3 Bootstrap Distributions and Standard Errors
Case 18.2 Real Estate Sale Prices
Bootstrap distributions of other statistics
Bootstrap t confidence intervals
Bootstrapping to compare two groups
Beyond the basics: the bootstrap for a scatterplot smoother
Section 18.3 Summary
Section 18.3 Exercises
18.4 How Accurate Is a Bootstrap Distribution?
Bootstrapping small samples
Bootstrapping a sample median
Section 18.4 Summary
Section 18.4 Exercises
18.5 Bootstrap Confidence Intervals
Bootstrap percentiles as a check
Confidence intervals for the correlation
Case 18.3 Baseball Salaries and Performance
More accurate bootstrap confidence intervals
Bootstrap tilting and BCa intervals
How BCa and tilting intervals work
Section 18.5 Summary
Section 18.5 Exercises
TABLE OF CONTENTS
18.6 Significance Testing Using Permutation Tests
Using software
Permutation tests in practice
Permutation tests in other settings
Section 18.6 Summary
Section 18.6 Exercises
Statistics in Summary
Chapter 18 Review Exercises |
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| index_date | 2024-07-02T21:13:17Z |
| indexdate | 2024-08-22T00:07:37Z |
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| language | English |
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| spelling | The practice of business statistics using data for decisions David S. Moore ... 2. ed. New York, NY Freeman 2009 getr. Zählung Ill., graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Statistik Commercial statistics Statistics Betriebsdaten (DE-588)4145038-3 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Betriebsdaten (DE-588)4145038-3 s Statistik (DE-588)4056995-0 s b DE-604 Moore, David S. Sonstige (DE-588)135745551 oth HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016556122&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | The practice of business statistics using data for decisions Statistik Commercial statistics Statistics Betriebsdaten (DE-588)4145038-3 gnd Statistik (DE-588)4056995-0 gnd |
| subject_GND | (DE-588)4145038-3 (DE-588)4056995-0 |
| title | The practice of business statistics using data for decisions |
| title_auth | The practice of business statistics using data for decisions |
| title_exact_search | The practice of business statistics using data for decisions |
| title_exact_search_txtP | The practice of business statistics using data for decisions |
| title_full | The practice of business statistics using data for decisions David S. Moore ... |
| title_fullStr | The practice of business statistics using data for decisions David S. Moore ... |
| title_full_unstemmed | The practice of business statistics using data for decisions David S. Moore ... |
| title_short | The practice of business statistics |
| title_sort | the practice of business statistics using data for decisions |
| title_sub | using data for decisions |
| topic | Statistik Commercial statistics Statistics Betriebsdaten (DE-588)4145038-3 gnd Statistik (DE-588)4056995-0 gnd |
| topic_facet | Statistik Commercial statistics Statistics Betriebsdaten |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016556122&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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