Modern business statistics with Microsoft Excel:
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Cincinnati, Ohio
South-Western College Pub.
2003
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009853523&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Beschreibung: | CD-ROM-Beil. u.d.T.: Microsoft Excel data files |
| Umfang: | XXIII, 936 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| ISBN: | 0324121741 |
Internformat
MARC
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| 100 | 1 | |a Anderson, David Ray |d 1941- |e Verfasser |0 (DE-588)122291565 |4 aut | |
| 245 | 1 | 0 | |a Modern business statistics with Microsoft Excel |c David R. Anderson, Dennis J. Sweeney, Thomas A. Williams |
| 246 | 1 | 3 | |a Microsoft Excel data files |
| 264 | 1 | |a Cincinnati, Ohio |b South-Western College Pub. |c 2003 | |
| 300 | |a XXIII, 936 S. |b Ill., graph. Darst. |e 1 CD-ROM (12 cm) | ||
| 336 | |b txt |2 rdacontent | ||
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| 500 | |a CD-ROM-Beil. u.d.T.: Microsoft Excel data files | ||
| 630 | 0 | 4 | |a Microsoft Excel for Windows |
| 650 | 4 | |a Commercial statistics | |
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| 700 | 1 | |a Williams, Thomas Arthur |d 1944- |e Sonstige |0 (DE-588)121277887 |4 oth | |
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Datensatz im Suchindex
| _version_ | 1819272651925880832 |
|---|---|
| adam_text | Chapter 1 Data and Statistics 1
Chapter 2 Descriptive Statistics: Tabular and Graphical Methods 26
Chapter 3 Descriptive Statistics: Numerical Methods 79
Chapter 4 Introduction to Probability 140
Chapter 5 Discrete Probability Distributions 184
Chapter 6 Continuous Probability Distributions 223
Chapter 7 Sampling and Sampling Distributions 254
Chapter 8 Interval Estimation 294
Chapter 9 Hypothesis Testing 335
Chapter 10 Statistical Inferences About Means and Proportions for Two
Populations 397
Chapter 11 Inferences About Population Variances 446
Chapter 12 Tests of Goodness of Fit and Independence 473
Chapter 13 Analysis of Variance and Experimental Design 505
Chapter 14 Simple Linear Regression 564
Chapter 15 Multiple Regression 644
Chapter 16 Regression Analysis: Model Building 696
Chapter 17 Nonparametric Methods 748
Chapter 18 Sample Survery 789
Chapter 19 Statistical Methods for Quality Control 829
Appendix A References and Bibliography 863
Appendix B Tables 864
Appendix C Summation Notation 874
Appendix D Answers to Even Numbered Exercises 876
Appendix E Solutions to Self Test Exercises 893
Appendix F Excel Functions and the Function Wizard 924
Index 929
Chapter 1
Data and Statistics 1
Statistics in Practice: Business Week 2
1.1 Applications in Business and Economics 3
Accounting 3
Finance 3
Marketing 4
Production 4
Economics 4
1.2 Data 4
Elements, Variables, and Observations 5
Scales of Measurement 6
Qualitative and Quantitative Data 7
Cross Sectional and Time Series Data 7
1.3 Data Sources 8
Existing Sources 8
Statistical Studies 10
Data Acquisition Errors 11
1.4 Descriptive Statistics 12
1.5 Statistical Inference 14
1.6 Statistical Analysis Using Microsoft Excel 16
Data Sets and Excel Worksheets 16
Using Excel for Statistical Analysis 18
Summary 19
Glossary 20
Exercises 20
Chapter 2
Descriptive Statistics: Tabular and Graphical Methods 26
Statistics in Practice: Colgate Palmolive Company 27
2.1 Summarizing Qualitative Data 28
Frequency Distribution 28
Using Excel s COUNTIF Function to Construct a Frequency Distribution 29
Relative Frequency and Percent Frequency Distributions 29
Using Excel to Construct Relative Frequency and Percent Frequency
Distributions 31
Bar Graphs and Pie Charts 32
Using Excel s Chart Wizard to Construct Bar Graphs and Pie Charts 33
Exercises 35
2.2 Summarizing Quantitative Data 37
Frequency Distribution 37
Using Excel s FREQUENCY Function to Construct a Frequency Distribution 39
Relative Frequency and Percent Frequency Distributions 40
Histogram 41
Using Excel s Chart Wizard to Construct a Histogram 42
Cumulative Distributions 43
Ogive 45
Exercises 47
2.3 Exploratory Data Analysis: The Stem and Leaf Display 50
Exercises 53
2.4 Crosstabulations and Scatter Diagrams 55
Crosstabulation 55
Using Excel s PivotTable Report to Construct a Crosstabulation 56
Scatter Diagram 60
Using Excel s Chart Wizard to Construct a Scatter Diagram 63
Exercises 64
Summary 67
Glossary 68
Key Formulas 69
Supplementary Exercises 69
Case Problem: Consolidated Foods 74
Appendix 2.1: Using Excel s Histogram Tool to Construct a Frequency
Distribution and Histogram 75
Chapter 3
Descriptive Statistics: Numerical Methods 79
Statistics in Practice: Small Fry Design 80
3.1 Measures of Location 81
Mean 81
Median 82
Mode 83
Using Excel to Compute the Mean, Median, and Mode 84
Percentiles 85
Quartiles 86
Using Excel to Sort Data and Using Excel to Compute Percentiles and Quartiles 87
Exercises 88
3.2 Measures of Variability 92
Range 93
Interquartile Range 93
Variance 93
Standard Deviation 96
Using Excel to Compute the Sample Variance and Sample Standard Deviation 96
Coefficient of Variation 97
Using Excel s Descriptive Statistics Tool 98
Exercises 99
3.3 Measures of Relative Location and Detecting Outliers 101
z Scores 102
Chebyshev s Theorem 102
Empirical Rule 103
Detecting Outliers 104
Exercises 105
3.4 Exploratory Data Analysis 107
Five Number Summary 107
Box Plot 108
Exercises 109
3.5 Measures of Association Between Two Variables 112
Covariance 113
Interpretation of the Covariance 114
Correlation Coefficient 116
Interpretation of the Correlation Coefficient 117
Using Excel to Compute the Covariance and Correlation Coefficient 118
Exercises 119
3.6 The Weighted Mean and Working with Grouped Data 121
Weighted Mean 122
Grouped Data 123
Exercises 125
Summary 127
Glossary 128
Key Formulas 129
Supplementary Exercises 130
Case Problem 1: Consolidated Foods, Inc. 135
Case Problem 2: National Health Care Association 136
Case Problem 3: Business Schools of Asia Pacific 137
Chapter 4
Introduction to Probability 140
Statistics in Practice: Morton International 141
4.1 Experiments, Counting Rules, and Assigning Probabilities 142
Counting Rules, Combinations, and Permutations 143
Assigning Probabilities 147
Probabilities for the KP L Project 149
Exercises 150
4.2 Events and Their Probabilities 152
Exercises 154
4.3 Some Basic Relationships of Probability 156
Complement of an Event 156
Addition Law 157
Exercises 160
4.4 Conditional Probability 161
Independent Events 164
Multiplication Law 165
Exercises 166
4.5 Bayes Theorem 169
Tabular Approach 172
Using Excel to Compute Posterior Probabilities 173
Exercises 174
Summary 175
Glossary 176
Key Formulas 177
Supplementary Exercises 178
Case Problem: Hamilton County Judges 182
Chapter 5
Discrete Probability Distributions 184
Statistics in Practice: Citibank 185
5.1 Random Variables 185
Discrete Random Variables 186
Continuous Random Variables 187
Exercises 187
5.2 Discrete Probability Distributions 188
Exercises 191
5.3 Expected Value and Variance 193
Expected Value 193
Variance 194
Using Excel to Compute the Expected Value, Variance, and Standard Deviation 195
Exercises 196
5.4 Binomial Probability Distribution 199
A Binomial Experiment 199
Martin Clothing Store Problem 201
Using Excel to Compute Binomial Probabilities 205
Expected Value and Variance for the Binomial Probability Distribution 206
Exercises 207
5.5 Poisson Probability Distribution 209
An Example Involving Time Intervals 210
An Example Involving Length or Distance Intervals 211
Using Excel to Compute Poisson Probabilities 211
Exercises 213
5.6 Hypergeometric Probability Distribution 215
Using Excel to Compute Hypergeometric Probabilities 216
Exercises 216
Summary 217
Glossary 218
Key Formulas 219
Supplementary Exercises 220
Chapter 6
Continuous Probability Distributions 223
Statistics in Practice: Procter Gamble 224
6.1 Uniform Probability Distribution 225
Area as a Measure of Probability 226
Exercises 228
6.2 Normal Probability Distribution 229
Normal Curve 229
Standard Normal Probability Distribution 231
Computing Probabilities for Any Normal Probability Distribution 237
Grear Tire Company Problem 238
Using Excel to Compute Normal Probabilities 240
Exercises 243
6.3 Exponential Probability Distribution 245
Computing Probabilities for the Exponential Distribution 246
Relationship Between the Poisson and Exponential Distributions 247
Using Excel to Compute Exponential Probabilities 248
Exercises 249
Summary 250
Glossary 250
Key Formulas 251
Supplementary Exercises 251
Chapter 7
Sampling and Sampling Distributions 254
Statistics in Practice: Mead Corporation 255
7.1 The Electronics Associates Sampling Problem 256
7.2 Simple Random Sampling 257
Sampling from Finite Population 257
Using Excel to Select a Simple Random Sample 259
Sampling from Infinite Population 261
Exercises 262
7.3 Point Estimation 264
Exercises 266
7.4 Introduction to Sampling Distributions 267
7.5 Sampling Distributions of x 271
Expected Value of x 271
Standard Deviation of x 272
Central Limit Theorem 273
Sampling Distribution of x for the EAI Problem 275
Practical Value of the Sampling Distribution of x 276
Relationship Between the Sample Size and the Sampling Distribution of x 277
Exercises 279
7.6 Sampling Distribution of p 281
Expected Value of p 282
Standard Deviation of p 282
Form of the Sampling Distribution of p 283
Practical Value of the Sampling Distribution of p 284
Exercises 285
7.7 Other Sampling Methods 287
Stratified Random Sampling 287
Cluster Sampling 288
Systematic Sampling 288
Convenience Sampling 288
Judgment Sampling 289
Summary 289
Glossary 290
Key Formulas 291
Supplementary Exercises 291
Chapter 8
Interval Estimation 294
Statistics in Practice: Dollar General Corporation 295
8.1 Interval Estimation of a Population Mean: Large Sample Case 296
CJW Problem 296
Large Sample Case with o Assumed Known 298
Large Sample Case with a Estimated by s 300
Using Excel to Construct a Confidence Interval: Large Sample Case 302
Exercises 304
8.2 Interval Estimation of a Population Mean: Small Sample Case 306
Small Sample Case with a Assumed Known 306
Small Sample Case with a Estimated by s 307
Using Excel to Construct a Confidence Interval: With a Estimated
bys 310
The Role of the Population Distribution 312
Exercises 315
8.3 Determining the Sample Size 317
Exercises 318
8.4 Interval Estimation of a Population Proportion 319
Using Excel to Construct a Confidence Interval 321
Determining the Sample Size 322
Exercises 324
Summary 326
Glossary 327
Key Formulas 327
Supplementary Exercises 328
Case Problem 1: Bock Investment Services 331
Case Problem 2: Gulf Real Estate Properties 331
Case Problem 3: Metropolitan Research, Inc. 334
Chapter 9
Hypothesis Testing 335
Statistics in Practice: Harris Corporation 336
9.1 Developing Null and Alternative Hypotheses 337
Testing Research Hypotheses 337
Testing the Validity of a Claim 337
Testing in Decision Making Situations 338
Summary of Forms for Null and Alternative Hypotheses 338
Exercises 339
9.2 Type I and Type H Errors 339
Exercises 341
9.3 One Tailed Tests About a Population Mean: Large Sample Case 342
One Tailed Tests: Large Sample Case with a Assumed Known 344
Use of p Values 346
Steps of Hypothesis Testing 347
One Tailed Tests: Large Sample Case with o Estimated by s 341
Using Excel to Conduct a One Tailed Hypothesis Test 349
Summary: One Tailed Tests About a Population Mean 352
Exercises 354
9.4 Two Tailed Tests About a Population Mean: Large Sample Case 356
p Values for Two Tailed Tests 357
Using Excel to Conduct a Two Tailed Hypothesis Test 358
Summary: Two Tailed Tests About a Population Mean 359
Relationship Between Interval Estimation and Hypothesis Testing 360
Exercises 362
9.5 Tests About a Population Mean: Small Sample Case 364
p Values and the t Distribution 366
Using Excel to Conduct a One Tailed Hypothesis Test: Small Sample Case 367
Two Tailed Test 369
Using Excel to Conduct a Two Tailed Hypothesis Test: Small Sample Case 369
Exercises 370
9.6 Tests About a Population Proportion 373
Using Excel to Conduct Hypothesis Tests About a Population Proportion 375
Exercises 378
9.7 Hypothesis Testing and Decision Making 380
9.8 Calculating the Probability of Type II Errors 381
Exercises 384
9.9 Determining the Sample Size for a Hypothesis Test About a Population
Mean 385
Exercises 388
Summary 389
Glossary 391
Key Formulas 392
Supplementary Exercises 392
Case Problem 1: Unemployment Study 395
Case Problem 2: Quality Associates, Inc. 395
Chapter 10
Statistical Inferences About Means and Proportions for Two
Populations 397
Statistics in Practice: Fisons Corporation 398
10.1 Estimation of the Difference Between the Means of Two Populations:
Independent Samples 399
Sampling Distribution of xx — x2 401
Large Sample Case 401
Using Excel: Large Sample Case 403
Small Sample Case 404
Using Excel: Small Sample Case 407
Exercises 408
10.2 Hypothesis Tests About the Difference Between the Means of Two Populations:
Independent Samples 411
Large Sample Case 411
Using Excel: Large Sample Case 414
Small Sample Case 416
Using Excel: Small Sample Case 418
Exercises 420
10.3 Inferences About the Difference Between the Means of Two Populations:
Matched Samples 423
Using Excel 426
Exercises 428
10.4 Inferences About the Difference Between the Proportions of Two
Populations 431
Sampling Distribution of px — p2 431
Interval Estimation of p, p2 432
Using Excel to Develop an Interval Estimate of px — p2 433
Hypothesis Tests About /?, — p2 434
Using Excel to Conduct a Hypothesis Test About px — p2 436
Exercises 437
Summary 439
Glossary 440
Key Formulas 440
Supplementary Exercises 442
Case Problem: Par, Inc. 444
Chapter 11
Inferences About Population Variances 446
Statistics in Practice: U.S. General Accounting Office 447
11.1 Inferences About a Population Variance 448
Interval Estimation of a2 448
Using Excel to Construct a Confidence Interval 452
Hypothesis Testing 453
Using Excel to Conduct a Hypothesis Test 457
Exercises 458
11.2 Inferences About the Variances of Two Populations 460
Using Excel to Conduct a Hypothesis Test 466
Exercises 467
Summary 469
Key Formulas 469
Supplementary Exercises 470
Case Problem: Air Force Training Program 471
Chapter 12
Tests of Goodness of Fit and Independence 473
Statistics in Practice: United Way 474
12.1 Goodness of Fit Test: A Multinomial Population 475
Using Excel to Conduct a Goodness of Fit Test 478
Exercises 479
12.2 Test of Independence 481
Using Excel to Conduct a Test of Independence 485
Exercises 486
12.3 Goodness of Fit Test: Poisson and Normal Distributions 489
Poisson Distribution 489
Using Excel to Conduct a Poisson Distribution Goodness of Fit Test 492
Normal Distribution 493
Using Excel to Conduct a Normal Distribution Goodness of Fit Test 497
Exercises 498
Summary 499
Glossary 499
Key Formulas 500
Supplementary Exercises 500
Case Problem: A Bipartisan Agenda for Change 503
Chapter 13
Analysis of Variance and Experimental Design 505
Statistics in Practice: Burke Marketing Services, Inc. 506
13.1 An Introduction to Analysis of Variance 506
Assumptions for Analysis of Variance 508
A Conceptual Overview 508
13.2 Analysis of Variance: Testing for the Equality of k Population
Means 510
Between Treatments Estimate of Population Variance 512
Within Treatments Estimate of Population Variance 512
Comparing the Variance Estimates: The F Test 513
ANOVA Table 514
Using Excel s Anova: Single Factor Tool 515
Exercises 518
13.3 Multiple Comparison Procedures 521
Fisher s LSD 521
Type I Error Rates 523
Exercises 524
13.4 Introduction to Experimental Design 525
Data Collection 526
13.5 Completely Randomized Designs 528
Between Treatments Estimate of Population Variance 528
Within Treatments Estimate of Population Variance 529
Comparing the Variance Estimates: The F Test 529
ANOVA Table 530
Using Excel s Anova: Single Factor Tool 530
Pairwise Comparisons 530
Exercises 532
13.6 Randomized Block Design 534
Air Traffic Controller Stress Test 535
ANOVA Procedure 536
Computations and Conclusions 537
Using Excel s Anova: Two Factor Without Replication Tool 539
Exercises 540
13.7 Factorial Experiments 542
ANOVA Procedure 544
Computations and Conclusions 544
Using Excel s Anova: Two Factor With Replication Tool 547
Exercises 549
Summary 552
Glossary 552
Key Formulas 553
Supplementary Exercises 555
Case Problem 1: Wentworth Medical Center 561
Case Problem 2: Compensation for ID Professionals 562
Chapter 14
Simple Linear Regression 564
Statistics in Practice: Polaroid Corporation 565
14.1 Simple Linear Regression Model 566
Regression Model and Regression Equation 566
Estimated Regression Equation 567
14.2 Least Squares Method 568
Using Excel to Develop a Scatter Diagram and Compute the Estimated
Regression Equation 573
Exercises 575
14.3 Coefficient of Determination 580
Using Excel to Compute the Coefficient of Determination 584
Correlation Coefficient 584
Exercises 586
14.4 Model Assumptions 588
14.5 Testing for Significance 590
Estimate of a2 590
fTest 591
Confidence Interval for /?[ 593
FTest 594
Some Cautions About the Interpretation of Significance Tests 596
Exercises 597
14.6 Excel s Regression Tool 599
Using Excel s Regression Tool for the Armand s Pizza Parlors Problem 599
Interpretation of Estimated Regression Equation Output 600
Interpretation of ANOVA Output 602
Interpretation of Regression Statistics Output 603
Exercises 603
14.7 Using the Estimated Regression Equation for Estimation
and Prediction 606
Point Estimation 606
Interval Estimation 607
Confidence Interval Estimate of the Mean Value of y 607
Prediction Interval Estimate of an Individual Value of y 608
Using Excel to Develop Confidence and Prediction Interval
Estimates 610
Exercises 612
14.8 Residual Analysis: Validating Model Assumptions 614
Residual Plot Against x 615
Using Excel s Regression Tool to Construct a Residual Plot 618
Standardized Residuals 618
Using Excel to Construct a Standardized Residual Plot 620
Normal Probability Plot 621
Exercises 623
14.9 Outliers and Influential Observations 625
Detecting Outliers 625
Detecting Influential Observations 626
Exercises 629
Summary 631
Glossary 631
Key Formulas 632
Supplementary Exercises 634
Case Problem 1: Spending and Student Achievement 639
Case Problem 2: U.S. Department of Transportation 641
Case Problem 3: Alumni Giving 642
Chapter 15
Multiple Regression 644
Statistics in Practice: Champion International Corporation 645
15.1 Multiple Regression Model 646
Regression Model and Regression Equation 646
Estimated Multiple Regression Equation 646
15.2 Least Squares Method 647
An Example: Butler Trucking Company 548
Using Excel s Regression Tool to Develop the Estimated Multiple Regression
Equation 649
Note on Interpretation of Coefficients 652
Exercises 653
15.3 Multiple Coefficient of Determination 657
Exercises 658
15.4 Model Assumptions 660
15.5 Testing for Significance 661
FTest 661
fTest 664
Multicollinearity 665
Exercises 666
15.6 Using the Estimated Regression Equation for Estimation and Prediction 668
Exercises 669
15.7 Qualitative Independent Variables 670
An Example: Johnson Filtration, Inc. 670
Interpreting the Parameters 673
More Complex Qualitative Variables 674
Exercises 675
15.8 Residual Analysis 678
Residual Plot Against y 678
Standardized Residual Plot Against y 680
Exercises 681
Summary 682
Glossary 683
Key Formulas 684
Supplementary Exercises 684
Case Problem 1: Consumer Research, Inc. 690
Case Problem 2: NFL Quarterback Rating 691
Case Problem 3: Predicting Student Proficiency Test Scores 692
Case Problem 4: Alumni Giving 693
Chapter 16
Regression Analysis: Model Building 696
Statistics in Practice: Monsanto Company 697
16.1 General Linear Model 698
Modeling Curvilinear Relationships 698
Interaction 700
Transformations Involving the Dependent Variable 704
Nonlinear Models That Are Intrinsically Linear 707
Exercises 708
16.2 Determining When to Add or Delete Variables 711
General Case 713 |
Use of p Values 714 |
Exercises 715 j
16.3 Analysis of a Larger Problem 718 !
16.4 Variable Selection Procedures 722 I
Stepwise Regression 722 ;
Forward Selection 723 i
Backward Elimination 723 !
Using Excel to Perform the Backward Elimination Procedure 723
Best Subsets Regression 725
Exercises 726
16.5 Residual Analysis 728
Autocorrelation and the Durbin Watson Test 729
Exercises 734
16.6 Multiple Regression Approach to Analysis of Variance and Experimental
Design 735
Exercises 738
Summary 739
Glossary 740
Key Formulas 740
Supplementary Exercises 740
Case Problem 1: Unemployment Study 744
Case Problem 2: Analysis of PGA Tour Statistics 745
Case Problem 3: Predicting Graduation Rates for Colleges and Universities 746
Chapter 17
Nonparametric Methods 748
i
Statistics in Practice: West Shell Realtors 749
17.1 Sign Test 751
Small Sample Case 751
Using Excel 753
Large Sample Case 754
Using Excel 756
Hypothesis Test About a Median 756
Using Excel 757
Exercises 759
17.2 Wilcoxin Signed Rank Test 760
Using Excel 763
Exercises 764
17.3 Mann Whitney Wilcoxin Test 766
Small Sample Case 767
Large Sample Case 769 !
Using Excel 772
Exercises 772
17.4 Kruskal Wallis Test 775
Using Excel 777
Exercises 778
17.5 Rank Correlation 780
Test for Significant Rank Correlation 780
Using Excel 782
Exercises 783
Summary 785
Glossary 785
Key Formulas 786
Supplementary Exercises 786
Chapter 18
Sample Survey 789
Statistics in Practice: Cinergy 790
18.1 Terminology Used in Sample Surveys 790
18.2 Types of Surveys and Sampling Methods 791
18.3 Survey Errors 793
Nonsampling Error 793
Sampling Error 793
18.4 Simple Random Sampling 794
Population Mean 794
Population Total 795
Population Proportion 797
Using Excel for Simple Random Sampling 797
Determining the Sample Size 799
Exercises 802
18.5 Stratified Simple Random Sampling 802
Population Mean 803
Using Excel: Population Mean 805
Population Total 806
Using Excel: Population Total 807
Population Proportion 807
Using Excel: Population Proportion 809
Determining the Sample Size 809
Exercises 812
18.6 Cluster Sampling 813
Population Mean 815
Population Total 817
Population Proportion 817
Using Excel for Cluster Sampling 819
Determining the Sample Size 819
Exercises 819
18.7 Systematic Sampling 821
Summary 821
Glossary 822
Key Formulas 823
Supplementary Exercises 826
Chapter 19
Statistical Methods for Quality Control 829
Statistics in Practice: Dow Chemical 830
19.1 Statistical Process Control 831
Control Charts 832
x Chart: Process Mean and Standard Deviation Known 833 I
x Chart: Process Mean and Standard Deviation Unknown 835
R Chart 838
Using Excel to Construct an R Chart and an x Chart 840
p Chart 843
np Chart 845
Interpretation of Control Charts 846
Exercises 846
19.2 Acceptance Sampling 848
KALI, Inc.: An Example of Acceptance Sampling 850
Computing the Probability of Accepting a Lot 850
Selecting an Acceptance Sampling Plan 852
Multiple Sampling Plans 854
Exercises 856
Summary 857
Glossary 857
Key Formulas 858
Supplementary Exercises 859
Appendix A
References and Bibliography 863
Appendix B
Tables 864
Appendix C
Summation Notation 874
Appendix D
Answers to Even Numbered Exercises 876
Appendix E
Solutions to Self Test Exercises 893
Appendix F
Excel Functions and the Function Wizard 924
Index 929
|
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| author | Anderson, David Ray 1941- |
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| discipline | Informatik |
| format | Book |
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| genre | (DE-588)4151278-9 Einführung gnd-content |
| genre_facet | Einführung |
| id | DE-604.BV014398199 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T11:03:53Z |
| institution | BVB |
| isbn | 0324121741 |
| language | English |
| lccn | 2001049276 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-009853523 |
| oclc_num | 144599401 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG |
| owner_facet | DE-473 DE-BY-UBG |
| physical | XXIII, 936 S. Ill., graph. Darst. 1 CD-ROM (12 cm) |
| publishDate | 2003 |
| publishDateSearch | 2003 |
| publishDateSort | 2003 |
| publisher | South-Western College Pub. |
| record_format | marc |
| spellingShingle | Anderson, David Ray 1941- Modern business statistics with Microsoft Excel Microsoft Excel for Windows Commercial statistics Betriebsstatistik (DE-588)4006211-9 gnd EXCEL (DE-588)4138932-3 gnd Deskriptive Statistik (DE-588)4070313-7 gnd Inferenzstatistik (DE-588)4247120-5 gnd |
| subject_GND | (DE-588)4006211-9 (DE-588)4138932-3 (DE-588)4070313-7 (DE-588)4247120-5 (DE-588)4151278-9 |
| title | Modern business statistics with Microsoft Excel |
| title_alt | Microsoft Excel data files |
| title_auth | Modern business statistics with Microsoft Excel |
| title_exact_search | Modern business statistics with Microsoft Excel |
| title_full | Modern business statistics with Microsoft Excel David R. Anderson, Dennis J. Sweeney, Thomas A. Williams |
| title_fullStr | Modern business statistics with Microsoft Excel David R. Anderson, Dennis J. Sweeney, Thomas A. Williams |
| title_full_unstemmed | Modern business statistics with Microsoft Excel David R. Anderson, Dennis J. Sweeney, Thomas A. Williams |
| title_short | Modern business statistics with Microsoft Excel |
| title_sort | modern business statistics with microsoft excel |
| topic | Microsoft Excel for Windows Commercial statistics Betriebsstatistik (DE-588)4006211-9 gnd EXCEL (DE-588)4138932-3 gnd Deskriptive Statistik (DE-588)4070313-7 gnd Inferenzstatistik (DE-588)4247120-5 gnd |
| topic_facet | Microsoft Excel for Windows Commercial statistics Betriebsstatistik EXCEL Deskriptive Statistik Inferenzstatistik Einführung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009853523&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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