Table of contents for Complete business statistics / Amir D. Aczel, Jayavel Sounderpandian.

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Note: Contents data are machine generated based on pre-publication provided by the publisher. Contents may have variations from the printed book or be incomplete or contain other coding.


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C O N T E N T S
Chapter 1 Introduction and Descriptive Statistics 22
1?1 Using Statistics 23
Samples and Populations 25
Data and Data Collection 25
1?2 Percentiles and Quartiles 28
1?3 Measures of Central Tendency 31
1?4 Measures of Variability 35
1?5 Grouped Data and the Histogram 40
1?6 Skewness and Kurtosis 43
1?7 Relations between the Mean and the Standard
Deviation 44
Chebyshev?s Theorem 44
The Empirical Rule 45
1?8 Methods of Displaying Data 45
Pie Charts 46
Bar Charts 46
Frequency Polygons and Ogives 46
A Caution about Graphs 47
Time Plots 49
1?9 Exploratory Data Analysis 51
Stem-and-Leaf Displays 51
Box Plots 52
1?10 Using the Computer 58
Percentile and Percentile Rank Computation 58
Histograms 58
Pie Charts 59
Bar Charts 59
Box Plots 60
Time Plots 60
Scatter Plots 61
1?11 Summary and Review of Terms 65
Case 1: NASDAQ Volatility 73
Chapter 2 Probability 74
2?1 Using Statistics 75
2?2 Basic Definitions: Events, Sample Space,
and Probabilities 77
2?3 Basic Rules for Probability 82
The Range of Values 82
The Rule of Complements 83
Mutually Exclusive Events 84
2?4 Conditional Probability 86
2?5 Independence of Events 91
Product Rules for Independent Events 93
2?6 Combinatorial Concepts 96
2?7 The Law of Total Probability and Bayes?
Theorem 99
The Law of Total Probability 99
Bayes? Theorem 101
2?8 The Joint Probability Table 105
2?9 Using the Computer 106
2?10 Summary and Review of Terms 109
Case 2: Job Applications 114
Chapter 3 Random Variables 116
3?1 Using Statistics 117
Discrete and Continuous Random Variables 121
Cumulative Distribution Function 122
3?2 Expected Values of Discrete Random Variables 128
The Expected Value of a Function of a Random Variable 129
Variance and Standard Deviation of a Random Variable 130
Variance of a Linear Function of a Random Variable 132
3?3 Sum and Linear Composites of Random Variables 133
Chebyshev?s Theorem 134
The Templates for Random Variables 135
The Use of Standard Random Variables 138
3?4 Bernoulli Random Variable 138
3?5 The Binomial Random Variable 139
Conditions for a Binomial Random Variable 140
Binomial Distribution Formulas 140
The Template 141
Problem Solving with the Template 141
3?6 Negative Binomial Distribution 144
Negative Binomial Distribution Formulas 145
Problem Solving with the Template 145
3?7 The Geometric Distribution 146
Geometric Distribution Formulas 146
Problem Solving with the Template 147
3?8 The Hypergeometric Distribution 147
Hypergeometric Distribution Formulas 148
Problem Solving with the Template 149
3?9 The Poisson Distribution 150
Problem Solving with the Template 151
3?10 Continuous Random Variables 152
3?11 Uniform Distribution 155
Problem Solving with the Template 156
3?12 The Exponential Distribution 156
A Remarkable Property 157
The Template 157
Value at Risk 159
3?13 Summary and Review of Terms 159
Case 3: Microchip Contract 170
Case 4: Cereal Promotion 171
Chapter Appendix: Excel Formulas for Some Standard
Distributions 172
Chapter 4 The Normal Distribution 174
4?1 Using Statistics 175
4?2 Properties of the Normal Distribution 176
4?3 The Template 178
Problem Solving with the Template 179
Finding Normal Probabilities Using the Tables 181
4?4 The Standard Normal Distribution 181
Finding Probabilities of the Standard Normal Distribution 181
Finding Values of Z Given a Probability 184
4?5 The Transformation of Normal Random Variables 186
Using the Normal Transformation 188
4?6 The Inverse Transformation 193
4?7 Normal Approximation of Binomial Distributions 197
4?8 Summary and Review of Terms 199
Case 5: Acceptable Pins 204
Case 6: Multicurrency Decision 204
Chapter Appendix: Excel Functions for a Normal
Distribution 205
Chapter 5 Sampling and Sampling Distributions 206
5?1 Using Statistics 207
5?2 Sample Statistics as Estimators of Population
Parameters 209
Obtaining a Random Sample 212
Other Sampling Methods 213
Nonresponse 214
5?3 Sampling Distributions 215
The Central Limit Theorem 218
The History of the Central Limit Theorem 223
The Standardized Sampling Distribution of the
Sample Mean When _ Is Not Known 223
The Sampling Distribution of the Sample Proportion P ?
224
5?4 Estimators and Their Properties 227
Applying the Concepts of Unbiasedness, Efficiency,
Consistency, and Sufficiency 229
5?5 Degrees of Freedom 230
5?6 The Template 235
5?7 Summary and Review of Terms 236
Case 7: Acceptance Sampling of Pins 240
Chapter 6 Confidence Intervals 242
6?1 Using Statistics 243
6?2 Confidence Interval for the Population Mean When
the Population Standard Deviation Is Known 244
The Template 249
6?3 Confidence Intervals for _ When _ Is Unknown?
The t Distribution 252
The t Distribution 257
6?4 Large-Sample Confidence Intervals for
the Population Proportion p 259
The Template 260
6?5 Confidence Intervals for the Population Variance 262
The Template 265
6?6 Sample-Size Determination 266
6?7 The Templates 269
Optimizing Population Mean Estimates 269
Determining the Optimal Half-Width 269
Using the Solver 270
Optimizing Population Proportion Estimates 271
6?8 Summary and Review of Terms 272
Case 8: Presidential Polling 275
Case 9: Privacy Problem 276
Chapter 7 Hypothesis Testing 278
7?1 Using Statistics 279
The Null Hypothesis 279
7?2 The Concepts of Hypothesis Testing 283
Evidence Gathering 283
Type I and Type II Errors 283
The p-Value 284
The Significance Level 285
Optimal _ and the Compromise between Type I
and Type II Errors 287
_ and Power 287
Sample Size 288
7?3 Computing the p-Value 289
The Test Statistic 289
p-Value Calculations 289
One-Tailed and Two-Tailed Tests 291
Computing _ 293
7?4 The Hypothesis Test 295
Testing Population Means 295
A Note on t Tables and p-Values 296
The Templates 297
Testing Population Proportions 300
Testing Population Variances 301
7?5 Pretest Decisions 312
Testing Population Means 313
Manual Calculation of Required Sample Size 314
Testing Population Proportions 317
Manual Calculation of Sample Size 319
7?6 Summary and Review of Terms 321
Case 10: Tiresome Tires I 322
Chapter 8 The Comparison of Two Populations 324
8?1 Using Statistics 325
8?2 Paired-Observation Comparisons 326
The Template 328
Confidence Intervals 329
The Template 330
8?3 A Test for the Difference between Two Population
Means Using Independent Random Samples 333
The Templates 336
Confidence Intervals 338
The Templates 340
Confidence Intervals 343
8?4 A Large-Sample Test for the Difference between Two
Population Proportions 346
Confidence Intervals 348
The Template 349
8?5 The F Distribution and a Test for Equality of Two
Population Variances 351
A Statistical Test for Equality of Two Population
Variances 354
The Templates 357
8?6 Summary and Review of Terms 359
Case 11: Tiresome Tires II 364
Chapter Appendix: Using Excel for Testing Difference in
Population Means 364
Chapter 9 Analysis of Variance 368
9?1 Using Statistics 369
9?2 The Hypothesis Test of Analysis of Variance 370
The Test Statistic 372
9?3 The Theory and the Computations of ANOVA 375
The Sum-of-Squares Principle 379
The Degrees of Freedom 382
The Mean Squares 383
The Expected Values of the Statistics MSTR and MSE
under the Null Hypothesis 383
The F Statistic 383
9?4 The ANOVA Table and Examples 385
9?5 Further Analysis 391
The Tukey Pairwise-Comparisons Test 393
Conducting the Tests 395
The Case of Unequal Sample Sizes, and
Alternative Procedures 396
The Template 396
9?6 Models, Factors, and Designs 397
One-Factor versus Multifactor Models 398
Fixed-Effects versus Random-Effects Models 398
Experimental Design 399
9?7 Two-Way Analysis of Variance 400
The Two-Way ANOVA Model 401
The Hypothesis Tests in Two-Way ANOVA 402
Sums of Squares, Degrees of Freedom, and
Mean Squares 403
The F Ratios and the Two-Way ANOVA Table 404
The Template 407
The Overall Significance Level 407
The Tukey Method for Two-Way Analysis 408
Extension of ANOVA to Three Factors 409
Two-Way ANOVA with One Observation per Cell 409
9?8 Blocking Designs 413
Randomized Complete Block Design 413
The Template 416
9?9 Summary and Review of Terms 417
Case 12: Uniform Uniforms 420
Case 13: Checking Out Checkout 421
Chapter Appendix: ANOVA Using Excel Commands 422
Chapter 10 Simple Linear Regression and Correlation 426
10?1 Using Statistics 427
Model Building 428
10?2 The Simple Linear Regression Model 429
10?3 Estimation: The Method of Least Squares 432
The Template 439
10?4 Error Variance and the Standard Errors
of Regression Estimators 442
Confidence Intervals for the Regression Parameters 445
10?5 Correlation 448
10?6 Hypothesis Tests about the Regression Relationship 452
Other Tests 455
10?7 How Good Is the Regression? 457
10?8 Analysis-of-Variance Table and an F Test of the
Regression Model 461
10?9 Residual Analysis and Checking for
Model Inadequacies 463
A Check for the Equality of Variance of the Errors 463
Testing for Missing Variables 464
Detecting a Curvilinear Relationship between Y and X 464
The Normal Probability Plot 465
10?10 Use of the Regression Model for Prediction 472
Point Predictions 473
Prediction Intervals 473
A Confidence Interval for the Average Y, Given a
Particular Value of X 475
10?11 The Solver Method for Regression 476
10?12 Linear Composites of Dependent Random Variables 479
The Case of Independent Random Variables 479
The Template 481
The Case of Dependent Random Variables 481
The Template 483
10?13 Summary and Review of Terms 484
Case 14: Return on Capital in Health Care 486
Case 15: Risk and Return 487
Chapter Appendix: The LINEST Function 488
Chapter 11 Multiple Regression 490
11?1 Using Statistics 491
11?2 The k-Variable Multiple Regression Model 493
The Estimated Regression Relationship 496
11?3 The F Test of a Multiple Regression Model 497
11?4 How Good Is the Regression? 501
11?5 Tests of the Significance of Individual
Regression Parameters 506
11?6 Testing the Validity of the Regression Model 517
Residual Plots 517
Standardized Residuals 519
The Normal Probability Plot 519
Outliers and Influential Observations 519
Lack of Fit and Other Problems 522
11?7 Using the Multiple Regression Model
for Prediction 524
The Template 526
Setting Recalculation to ?Manual? on the Template 526
11?8 Qualitative Independent Variables 527
Interactions between Qualitative and Quantitative
Variables 534
11?9 Polynomial Regression 537
Other Variables and Cross-Product Terms 541
11?10 Nonlinear Models and Transformations 545
Variance-Stabilizing Transformations 551
Regression with Dependent Indicator Variable 552
11?11 Multicollinearity 555
Causes of Multicollinearity 556
Detecting the Existence of Multicollinearity 557
Solutions to the Multicollinearity Problem 561
11?12 Residual Autocorrelation and the
Durbin-Watson Test 563
11?13 Partial F Tests and Variable Selection Methods 566
Partial F Tests 566
Variable Selection Methods 569
11?14 Multiple Regression Using the Solver 572
A Comment on R2 573
11?15 Summary and Review of Terms 574
Case 16: Return on Capital for Four Different Sectors 576
Chapter Appendix: LINEST Function for Multiple
Regression 579
Chapter 12 Time Series, Forecasting, and Index Numbers 582
12?1 Using Statistics 583
12?2 Trend Analysis 585
12?3 Seasonality and Cyclical Behavior 590
12?4 The Ratio-to-Moving-Average Method 593
The Template 598
The Cyclical Component of the Series 598
Forecasting a Multiplicative Series 599
12?5 Exponential Smoothing Methods 602
The Template 606
12?6 Index Numbers 607
The Consumer Price Index 610
The Template 612
12?7 Summary and Review of Terms 613
Case 17: Auto Parts Sales Forecast 615
Chapter 13 Quality Control and Improvement 616
13?1 Using Statistics 617
13?2 W. Edwards Deming Instructs 618
13?3 Statistics and Quality 619
Deming?s 14 Points 619
Process Capability 620
Control Charts 620
Pareto Diagrams 623
The Template 624
Acceptance Sampling 624
Analysis of Variance and Experimental Design 624
Taguchi Methods 625
13?4 The Chart 626
The Template 628
13?5 The R Chart and the s Chart 630
The R Chart 630
The s Chart 630
13?6 The p Chart 633
The Template 634
13?7 The c Chart 635
The Template 636
13?8 The x Chart 637
13?9 Summary and Review of Terms 637
Case 18: Quality Control and Improvement
at Nashua Corporation 638
Chapter 14 Nonparametric Methods and Chi-Square Tests 640
14?1 Using Statistics 641
14?2 The Sign Test 642
14?3 The Runs Test?A Test for Randomness 647
Large-Sample Properties 648
The Template 649
The Wald-Wolfowitz Test 649
14?4 The Mann-Whitney U Test 652
The Computational Procedure 653
The Template 657
14?5 The Wilcoxon Signed-Rank Test 659
The Paired-Observations Two-Sample Test 659
Large-Sample Version of the Test 660
A Test for the Mean or Median of a Single Population 661
The Template 663
14?6 The Kruskal-Wallis Test?A Nonparametric
Alternative to One-Way ANOVA 665
The Template 667
Further Analysis 669
14?7 The Friedman Test for a Randomized
Block Design 672
The Template 674
14?8 The Spearman Rank Correlation Coefficient 676
The Template 678
14?9 A Chi-Square Test for Goodness of Fit 680
A Goodness-of-Fit Test for the Multinomial Distribution 682
The Templates 683
Unequal Probabilities 683
The Template 686
14?10 Contingency Table Analysis?A Chi-Square Test
for Independence 688
The Template 691
14?11 A Chi-Square Test for Equality of Proportions 694
The Median Test 696
14?12 Summary and Review of Terms 699
Case 19: The Nine Nations of North America 701
Chapter 15 Bayesian Statistics and Decision Analysis 704
15?1 Using Statistics 705
15?2 Bayes? Theorem and Discrete Probability
Models 706
The Template 710
15?3 Bayes? Theorem and Continuous
Probability Distributions 713
The Normal Probability Model 714
Credible Sets 716
The Template 716
15?4 The Evaluation of Subjective Probabilities 719
Assessing a Normal Prior Distribution 719
15?5 Decision Analysis: An Overview 720
Actions 721
Chance Occurrences 721
Probabilities 722
Final Outcomes 722
Additional Information 722
Decision 722
15?6 Decision Trees 723
The Payoff Table 724
15?7 Handling Additional Information Using
Bayes? Theorem 732
Determining the Payoffs 734
Determining the Probabilities 734
15?8 Utility 743
A Method of Assessing Utility 745
15?9 The Value of Information 746
15?10 Using the Computer 749
The Template 749
15?11 Summary and Review of Terms 751
Case 20: Pizzas ?R? Us 753
Case 21: New Drug Development 754
Appendix A References 758
Appendix B Answers to Most Odd-Numbered Problems 761
Appendix C Statistical Tables 773
On the CD
Chapter 16 Sampling Methods
16?1 Using Statistics
16?2 Nonprobability Sampling and Bias
16?3 Stratified Random Sampling
Practical Applications
Confidence Intervals
The Template
Stratified Sampling for the Population Proportion
The Template
What Do We Do When the Population Strata
Weights Are Unknown?
How Many Strata Should We Use?
Postsampling Stratification
Optimum Allocation
The Template
16?4 Cluster Sampling
The Relation with Stratified Sampling
Single-Stage Cluster Sampling for the Population Mean
Single-Stage Cluster Sampling for the Population
Proportion
The Templates
Two-Stage Cluster Sampling
16?5 Systematic Sampling
The Advantages of Systematic Sampling
Estimation of the Population Mean in Systematic
Sampling
The Template
16?6 Nonresponse
16?7 Summary and Review of Terms
Case 22: The Boston Redevelopment Authority
Chapter 17 Multivariate Analysis
17?1 Using Statistics
17?2 The Multivariate Normal Distribution
17?3 Discriminant Analysis
Developing a Discriminant Function
Evaluating the Performance of the Model
Discriminant Analysis with More than Two Groups
17?4 Principal Components and Factor Analysis
Principal Components
The Extraction of the Components
Factor Analysis
The Extraction of Factors
The Rotation of Factors
17?5 Using the Computer
17?6 Summary and Review of Terms
Case 23: Predicting Company Failure
Index 811

Library of Congress Subject Headings for this publication:

Commercial statistics.
Statistics.