Engineering statistics:
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Englewood Cliffs, N.J.
Prentice-Hall
1972
|
| Edition: | 2.ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Physical Description: | XVIII,641 S. |
| ISBN: | 0132794551 |
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MARC
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| 100 | 1 | |a Bowker, Albert H. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Engineering statistics |c Albert H. Bowker ; Gerald J. Lieberman* |
| 250 | |a 2.ed. | ||
| 264 | 1 | |a Englewood Cliffs, N.J. |b Prentice-Hall |c 1972 | |
| 300 | |a XVIII,641 S. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
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| 650 | 4 | |a Ingénierie - Méthodes statistiques | |
| 650 | 4 | |a Mathématiques de l'ingénieur | |
| 650 | 7 | |a Statistiek |2 gtt | |
| 650 | 4 | |a Ingenieurwissenschaften | |
| 650 | 4 | |a Statistik | |
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Record in the Search Index
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| adam_text | CONTENTS
Chapter 1 Histograms and Empirical Distributions 1
1.1 Introduction 1
1.2 Empirical Distributions 2
1.3 Measures of Central Tendency 7
1.4 Measures of Variation 8
* 1.S Computation of the Mean and Standard Deviation of the Data from
the Frequency Table 9
Chapter 2 Random Variables and Probability Distributions 13
2.1 Introduction 13
2.2 Set of All Possible Outcomes of the Experiment—the Sample Space 14
2.3 Events 18
2.4 Random Variables 19
2.5 Probability 24
2.6 Cumulative Distribution Functions 27
2.7 Discrete Probability Distributions 33
2.8 Continuous Random Variables and Density Functions 37
2.9 Expectation 43
2.10 Moments 47
2.11 Some Properties of Functions of Random Variables 51
2.12 Bivariate Probability Distributions 52
2.13 Conditional Probability and Independent Events 57
2.14 Independent Random Variables and a Random Sample 60
2.15 Conditional Probability Distributions 64
Chapter 3 The Normal Distribution 75
3.1 Definitions 75
3.2 The Mean and Variance of the Normal Distribution 76
*3.2.1. Evaluation of the Mean and Variance 78
3.3 Tables of the Normal Integral 79
3.4 Combinations of Normally Distributed Variables 82
3.5 The Standardized Normal Random Variable 84
Y
vi ENGINEERING STATISTICS
3.6 The Distribution of the Sample Mean 84
3.7 Tolerances 86
* 3.8 Tolerances in Complex Items 93
3.9 The Central Limit Theorem 99
Chapter 4 Other Probability Distributions 106
4.1 Introduction 106
4.2 The Cm Square Distribution 107
4.2.1. The Chi Square Random Variable 107
4.2.2 The Addition Theorem 110
4.2.3 The Distribution of the Sample Variance, S2 111
4.3 The t Distribution 114
4.3.1 The t Random Variable _ 114
4.3.2 The Distribution of (X fi)y/n/S 117
4.3.3 The Distribution of the Difference Between Two Sample
Means 118
4.4 The F Distribution 120
4.4.1 The F Random Variable 120
4.4.2 The Distribution of the Ratio of Two Sample Variances 122
4.5 The Binomial Distribution 123
4.5.1 The Binomial Random Variable 123
*4.5.2 Tables of the Binomial Probability Distribution 126
*4.5.3 The Normal Approximation to the Binomial 127
*4.5.4 The Arc Sine Transformation 128
*4.5.S The Poisson Approximation to the Binomial 128
Chapter 5 Decision Making 134
5.1 Introduction 134
5.2 Decision Making Without Experimentation 134
5.2.1 Action Space 135
5.2.2 States of Nature 136
5.2.3 Loss Function 137
5.2.4 Criteria for Choosing Among Actions 138
5.2.5 Bayes Principle 139
5.2.6 Evaluation of the Loss Function for the Rockwell Hard¬
ness Example 141
5.2.7 Further Examples 145
5.3 Decision Making With Experimentation 148
5.3.1 Decision Procedures 148
5.3.2 Risk Function 150
5.3.3 Bayes Decision Procedures 152
5.3.4 Calculation of the Posterior Distribution 155
*5.3.4.1 Derivation of Posterior Distribution 158
5.3.5 Further Examples 158
5.3.6 Assessment of the Bayesian Approach 161
5.4 Significance Tests 163
5.4.1 The Operating Characteristic Curve 165
5.4.2 Comparison of the OC Curve with the Risk Function 167
5.4.3 Comparison of OC Curves 168
5.4.4 Tests of Hypotheses 172
5.4.5 One and Two Sided Procedures 174
CONTENTS VU
Chapter 6 Tests of Hypotheses about a Single Parameter 183
6.1 Test of the Hypothesis that the Mean of a Normal Distribution
Has a Specified Value when the Standard Deviation Is Known 183
6.1.1 Choice of an OC Curve 183
6.1.2 Tables and Charts for Determining Decision Rules 184
6.1.2.1 Tables and Charts for Two Sided
Procedures 185
6.1.2.2 Summary for Two Sided Procedures Using
Tables and Charts 188
6.1.2.3 Tables and Charts for One Sided Procedures 189
6.1.2.4 Summary for One Sided Procedures Using
Tables and Charts 191
6.1.2.5 Tables and Charts for OC Curves 192
6.1.3 Analytical Determination of Decision Rules 192
6.1.3.1 Acceptance Regions and Sample Sizes 192
6.1.3.2 The OC Curve 196
6.1.4 Example 197
6.2. Test of the Hypothesis that the Mean of a Normal Distribution
Has a Specified Value when the Standard Deviation is Unknown 198
6.2.1 Choice of an OC Curve 198
6.2.2 Tables and Charts for Carrying Out t Tests 199
6.2.2.1 Tables and Charts for Two Sided Procedures 200
6.2.2.2 Summary for Two Sided Procedures 200
6.2.2.3 Tables and Charts for One Sided Procedures 202
6.2.2.4 Summary for One Sided Procedures 204
6.2.2.5 Tables and Charts for OC Curves 205
6.2.3. Examples of t Tests 206
6.3 Test of the Hypothesis that the Standard Deviation of a Normal
Distribution Has a Specified Value 207
6.3.1 Choice of an OC Curve 207
6.3.2 Charts and Tables to Design Tests of Dispersion 208
6.3.2.1 Tables and Charts for Two Sided Procedures 208
6.3.2.2 Summary for Two Sided Procedures Using
Tables and Charts 209
6.3.2.3 Tables and Charts for One Sided Procedures 210
6.3.2.4 Summary for One Sided Procedures Using
Tables and Charts 213
6.3.2.5 Tables and Charts for OC Curves 214
6.3.3 Analytical Treatment for Chi Square Tests 215
6.3.4 Example 216
Chapter 7 Tests of Hypotheses about Two Parameters 225
7.1 Test of the Hypothesis that the Means of Two Normal Distribu¬
tions Are Equal when Both Standard Deviations Are Known 225
7.1.1 Choice of an OC Curve 225
7.1.2 Tables and Charts for Determining Decision Rules 226
7.1.2.1 Tables and Charts for Two Sided Procedures 226
7.1.2.2 Summary for Two Sided Procedures Using
Tables and Charts 228
Vffi ENGINEERING STATISTICS
7.1.2.3 Summary for One Sided Procedures Using
Tables and Charts 229
7.1.2.4 Tables and Charts for OC Curves 230
7.1.3 Analytical Determination of Decision Rules 230
7.1.3.1. Acceptance Regions and Sample Sizes 230
7.1.3.2 The OC Curve 232
7.1.4 Example 234
7.2 Test of the Hypothesis that the Means of Two Normal Distribu¬
tions Are Equal, Assuming that the Standard Deviations Are Un¬
known but Equal 235
7.2.1 Choice of an OC Curve 235
7.2.2 Tables and Charts for Carrying out Two Sample t Tests 235
7.2.2.1 Tables and Charts for Two Sided Procedures 236
7.2.2.2 Summary for Two Sided Procedures Using
Tables and Charts 237
7.2.2.3 Summary for One Sided Procedures Using
Tables and Charts 237
7.2.2.4 Tables and Charts for OC Curves 238
7.2.3 Example 239
73 Test of the Hypothesis that the Means of Two Normal Distribu¬
tions Are Equal, Assuming that the Standard Deviations Are
Unknown and Not Necessarily Equal 240
7.3.1 Test Procedure 240
7.3.2 Example 241
7.4 Test for Equality of Means when the Observations Are Paired 242
7.4.1 Test Procedure 242
7.4.2 Example 244
7.5 Non parametric Tests 246
7.5.1 The Sign Test 246
7.5.2 The Wilcoxon Signed Rank Test 249
7.5.3 Wilcoxon Test for Two Independent Samples 251
7.6 Test of the Hypothesis that the Standard Deviations of Two
Normal Distributions Are Equal 254
7.6.1 Choice of an OC Curve 254
7.6.2 Charts and Tables for Carrying out F Tests 255
7.6.2.1 Tables and Charts for Two Sided Procedures 255
7.6.2.2 Summary for Two Sided Procedures Using
Tables and Charts 256
7.6.2.3 Tables and Charts for One Sided Procedures 257
7.6.2.4 Summary for One Sided Procedures Using
Tables and Charts 258
7.6.2.5 Tables and Charts for OC Curves 258
*7.63 Analytical Treatment for Tests 260
7.6.4 Example 262
7.7 Cochran s Test for the Homogeneity of Variances 263
Chapter 8 Estimation 279
8.1 Introduction 279
8.2 Point Estimation 279
8.2.1 Comparison of Estimators 280
CONTENTS iX
8.2.2 Unbiased Estimators 283
8.2.3 Consistent Estimators 284
8.2.4 Efficient Unbiased Estimators 285
8.2.5 Estimation by the Method of Maximum Likelihood 286
8.2.6 Estimation by the Method of Moments 290
8.2.7 Estimation by the Method of Bayes 292
8.3 Confidence Interval Estimation 294
8.3.1 Confidence Interval for the Mean of a Normal Distribu¬
tion when the Standard Deviation Is Known 295
8.3.2 Confidence Interval for the Mean of a Normal Distribu¬
tion when the Standard Deviation Is Unknown 296
8.3.3 Confidence Interval for the Standard Deviation of a Nor¬
mal Distribution 297
8.3.4 Confidence Interval for the Difference between the Means
of Two Normal Distributions when the Standard De¬
viations Are Both Known 298
8.3.5 Confidence Interval for the Difference between the Means
of Two Normal Distributions where the Standard Devia
ations Are Both Unknown but Equal 300
8.3.6 Confidence Interval for the Ratio of Standard Deviations
of Two Normal Distributions 301
8.3.7 A Table of Point Estimates and Interval Estimates 302
8.3.8 Approximate Confidence Intervals 302
8.3.9 Simultaneous Confidence Intervals 304
8.3.10 Bayesian Intervals 308
8.4 Statistical Tolerance Limits 309
8.4.1 Statistical Tolerance Limits Based on the Normal Dis¬
tribution 309
8.4.2 One Sided Statistical Tolerance Limits Based on the Nor¬
mal Distribution 310
8.4.3 Distribution Free Tolerance Limits 310
Chapter 9 Fitting Straight Lines 325
9.1 Introduction 325
9.2 Types of Linear Relationships 328
9.3 Least Squares Estimators of the Slope and Intercept 331
9.3.1 Formulation of the Problem and Results 331
*9.3.2 Theory 333
9.4 Confidence Interval Estimators of the Slope and Intercept 336
9.4.1 Formulation of the Problem and Results 336
*9.4.2 Theory 337
9.5 Point Estimators and Confidence Interval Estimators of the Aver¬
age Value of Y for a Given x 338
9.5.1 Formulation of the Problem and Results 338
*9.5.2 Theory 339
9.6 Point Estimators and Interval Estimators of the Independent Vari
iable x Associated with an Observation on the Dependent Vari¬
able Y 340
9.7 Prediction Interval for a Future Observation on the Dependent
Variable 342
X ENGINEERING STATISTICS
9.7.1 Formulation of the Problem and Results 342
*9.7.2 Theory 343
9.8 Tests of Hypotheses about the Slope and Intercept 345
9.9 Estimation of the Slope B when A Is Known to be Zero 346
9.10 Ascertaining Linearity 349
9.11 Transformation to a Straight Line 351
9.12 Work Sheets for Fitting Straight Lines 352
9.13 Illustrative Examples 352
9.14 Correlation 362
Chapter 10 Analysis of Variance 377
10.1 Introduction 377
10.2 Model for the One Way Classification 377
10.2.1 Fixed Effects Model 377
10.2.2 Random Effects Model 380
10.2.3 Further Examples of Fixed Effects and of the Random
Effects Models 380
10.2.4 Computational Procedure, One Way Classification 381
10.2.5 The Analysis of Variance Procedure 383
10.2.5.1 A Heuristic lustification 383
*10.2.5.2 The Partition Theorem 383
10.2.6 Analysis of the Fixed Effects Model, One Way Clas¬
sification 385
10.2.7 The OC Curve of the Analysis of Variance for the Fixed
Effects Model 389
10.2.8 Example Using the Fixed Effects Model 395
10.2.9 Analysis of the Random Effects Model 396
10.2.10 The OC Curve for the Random Effects Model 397
10.2.11 Example Using the Random Effects Model 402
10.2.12 Randomization Tests in the Analysis of Variance 403
10.3 Two Way Analysis of Variance, One Observation per Combina¬
tion 405
103.1 Fixed Effects Model 405
103.2 Random Effects Model 408
10.3.3 Mixed Fixed Effects and Random Effects Model 409
10.3.4 Computational Procedure, Two Way Classification, One
Observation per Combination 409
10.3.5 Analysis of the Fixed Effects Model, Two Way Clas¬
sification, One Observation per Combination 411
10.3.6 The OC Curve of the Analysis of Variance for the Fixed
Effects Model, Two Way Classification, One Observation
per Combination 413
10.3.7 Example Using the Fixed Effects Model 414
10.3.8 Analysis of the Random Effects Model, Two Way Clas¬
sification, One Observation per Combination 416
103.9 The OC Curve for the Random Effects Model, Two Way
Classification 417
10.3.10 Example Using the Random Effects Model 418
103.11 Analysis of the Mixed Effects Model, Two Way Clas¬
sification, One Observation per Combination 418
CONTENTS Xi
10.3.12 The ,OC Curve of the Analysis of Variance for the Mixed
Effects Model, Two Way Classification, One Observation
per Cell 420
10.3.13 Example Using the Mixed Effects Model 420
10.4 Two Way Analysis of Variance, n Observations per Combination 421
10.4.1 Description of the Various Models 421
10.4.2 Computational Procedure, Two Way Classification, n Ob¬
servations per Combination 423
10.4.3 Analysis of the Fixed Effects Model, Two Way Classifica¬
tion, n Observations per Combination 424
10.4.4 The OC Curve of the Analysis of Variance for the Fixed
Effects Model, Two Way Classification, n Observations
per Cell 427
10.4.5 Example Using the Fixed Effects Model, Two Way Clas¬
sification, Three Observations per Combination 428
10.4.6 Analysis of the Random Effects Model, Two Way Clas¬
sification, n Observations per Combination 430
10.4.7 The OC Curve of the Random Effects Model, Two Way
Classification, n Observations per Combination 431
10.4.8 Example Using the Random Effects Model 432
10.4.9 Analysis of the Mixed Effects Model, Two Way Clas¬
sification, n Observations per Cell 432
10.4.10 The OC Curve of the Analysis of Variance for the Mixed
Effects Model, Two Way Classification, n Observations
per Cell 434
10.4.11 Example Using the Mixed Effects Model 434
10.5 Summary of Models and Tests 436
Chapter 11 Some Further Techniques of Data Analysis 452
11.1 Introduction 452
11.2 Qualitative Techniques for Determining the Form of a Distribu¬
tion 452
11.3 Quantitative Techniques for Determining the Form of a Distribu¬
tion 454
11.3.1 The Kolmogorov Smirnov Test 454
11.3.2 The Chi Square Goodness of Fit Test 458
11.4 Chi Square Tests 460
11.4.1 The Hypothesis Completely Specifies the Theoretical
Frequency 461
11.4.2 Dichotomous Data 461
11.4.3 Test of Independence in a Two Way Table 463
11.4.4 Computing Form for Test of Independence in a 2 X 2
Table 464
11.5 Comparison of Two Percentages 465
11.6 Confidence Intervals for Proportion 466
Chapter 12 Statistical Quality Control: Control Charts 472
12.1 Introduction 472
12.2 An Overview of Control Charts 473
xii ENGINEERING STATISTICS
12.3 Control Chart for Variables: X Charts 474
123.1 Statistical Concepts 474
123.2 Estimate of X 475
12.3.3 Estimate of a by r 476
12.3.4 Estimate of a by K 476
12.3.5. Starting a Control Chart for T 478
123.6 Relation between Natural Tolerance Limits and Speci¬
fication Limits 479
123.7 Interpretation of Control Charts for ~X 480
12.4 R Charts and r Charts 481
12.4.1 Statistical Concepts 481
12.4.2 Setting up a Control Chart for R or a 483
12.5 Example of X and R Chart 483
12.6 Control Chart For Fraction Defective 485
12.6.1 Relation between Control Charts Based on Variables
Data and Charts Based on Attributes Data 485
12.6.2 Statistical Theory 486
12.6.3 Starting the Control Chart 487
12.6.4 Continuing the p Chart 488
12.6.5 Example 489
12.7 Control Charts For Defects 489
12.7.1 Difference between a Defect and a Defective Item 489
12.7.2 Statistical Theory 490
12.73 Starting and Continuing the c Chart 490
12.7.4 Example 491
12.8 Further Developments on Control Charts 492
12.8.1 The Signed Sequential Rank Control Chart 493
12.8.2 The Cumulative Sum Control Chart 495
Chapter 13 Sampling Inspection by Attributes 503
13.1 The Problem of Sampling Inspection 503
13.1.1 Introduction 503
13.1.2 Drawing the Sample 504
13.2 Lot by Lot Sampling Inspection by Attributes 505
13.2.1 Single Sampling Plans 505
13.2.1.1 Single Sampling 505
13.2.1.2 Choosing a Sampling Plan 507
13.2.13 Calculation of OC Curves for Single Sampling
Plans 507
13.2.1.4 Example 508
13.2.2 Double Sampling Plans 508
13.2.2.1 Double Sampling 508
*13.2.2.2 OC Curves for Double Sampling Plans 509
*13.2.23 Example 509
13.23 Multiple Sampling Plans 510
13.2.4 Classification of Sampling Plans 511
13.2.4.1 Classification By AQL 511
13.2.4.2 Classification By LTPD 512
13.2.4.3 Classification By Point of Control 512
13.2.4.4 Classification By AOQL 512
CONTENTS Xifl
13.2.5 Dodge Romig Tables 513
13.2.5.1 Single Sampling Lot Tolerance Tables 514
13.2.5.2 Double Sampling Lot Tolerance Tables 514
13.2.5.3 Single Sampling AOQL Tables 518
13.2.5.4 Double Sampling AOQL Tables 518
13.2.6 Military Standard 105D 518
13.2.6.1 History 518
13.2.6.2 Classification of Defects 522
13.2.6.3 Acceptable Quality Levels 522
13.2.6.4 Normal, Tightened, and Reduced Inspection 523
13.2.6.5 Sampling Plans 525
13.2.6.6 Summary of the Procedure To Be Followed in
the Selection of a Sampling Plan from MIL
STD 105D 527
13.2.7 Designing Your Own Attribute Plan 527
13.2.7.1 Computing the OC Curve of a Single Sampling
Plan 527
13.2.7.2 Finding a Sampling Plan Whose OC Curve
Passes through Two Points 537
13.2.7.3 Design of Item by Item Sequential Plans 537
13.2.8 A Bayesian Approach to Sampling Inspection 545
13.2.8.1 Economic Structure 545
13.2.8.2 A Decision Analysis Model 546
13.2.8.3 Bayes Procedures 547
13.3 Continuous Sampling Inspection 550
13.3.1 Introduction 550
13.3.2 Dodge Continuous Sampling Plans 551
13.3.3 Multi Level Sampling Plans 552
13.3.4 The Dodge CSP 1 Plan without Control 556
13.3.5 Wald Wolfowitz Continuous Sampling Plans 557
13.3.6 Girshick Continuous Sampling Plan 558
13.3.7 Plans Which Provide for Termination of Production 559
Chapter 14 Lot by Lot Sampling Inspection by Variables 565
14.1 Introduction 565
14.2 General Inspection Criteria 566
14.3 Estimates of the Percent Defective 568
14.3.1 Estimate of the Percent Defective when the Standard
Deviation Is Unknown but Estimated by the Sample
Standard Deviation 568
14.3.2 Estimate of the Percent Defective when the Standard
Deviation Is Unknown but Estimated by the Average
Range 569
14.3.3 Estimate of the Percent Defective when the Standard
Deviation Is Known 571
14.4 Comparison of Variables Procedures with M and k 574
14.5 The Military Standard for Inspection by Variables, MIL STD 414 575
14.5.1 Introduction 575
14.5.2 Section A — General Description of Sampling Plans 576
14.5.3 Section B— Variability Unknown, Standard Deviation
Method 585
Xiv ENGINEERING STATISTICS
14.5.4 Section C — Variability Unknown, Range Method 585
14.5.5 Section D — Variability Known 590
14.5.6 Example Using MIL STD 414 591
Appendix 599
Answers to Selected Problems 618
Index 623
|
| any_adam_object | 1 |
| author | Bowker, Albert H. Lieberman, Gerald J. 1925- |
| author_GND | (DE-588)111670195 |
| author_facet | Bowker, Albert H. Lieberman, Gerald J. 1925- |
| author_role | aut aut |
| author_sort | Bowker, Albert H. |
| author_variant | a h b ah ahb g j l gj gjl |
| building | Verbundindex |
| bvnumber | BV003030228 |
| callnumber-first | T - Technology |
| callnumber-label | TA153 |
| callnumber-raw | TA153 |
| callnumber-search | TA153 |
| callnumber-sort | TA 3153 |
| callnumber-subject | TA - General and Civil Engineering |
| classification_rvk | QH 231 QH 232 SK 850 |
| ctrlnum | (OCoLC)636592449 (DE-599)BVBBV003030228 |
| dewey-full | 620/.001/5195 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 620 - Engineering and allied operations |
| dewey-raw | 620/.001/5195 |
| dewey-search | 620/.001/5195 |
| dewey-sort | 3620 11 45195 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mathematik Wirtschaftswissenschaften |
| edition | 2.ed. |
| format | Book |
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| id | DE-604.BV003030228 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-09T15:52:30Z |
| institution | BVB |
| isbn | 0132794551 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-001897615 |
| oclc_num | 636592449 |
| open_access_boolean | |
| owner | DE-384 DE-739 DE-355 DE-BY-UBR DE-83 DE-706 |
| owner_facet | DE-384 DE-739 DE-355 DE-BY-UBR DE-83 DE-706 |
| physical | XVIII,641 S. |
| psigel | TUB-nveb |
| publishDate | 1972 |
| publishDateSearch | 1972 |
| publishDateSort | 1972 |
| publisher | Prentice-Hall |
| record_format | marc |
| spelling | Bowker, Albert H. Verfasser aut Engineering statistics Albert H. Bowker ; Gerald J. Lieberman* 2.ed. Englewood Cliffs, N.J. Prentice-Hall 1972 XVIII,641 S. txt rdacontent n rdamedia nc rdacarrier Ingénierie - Méthodes statistiques Mathématiques de l'ingénieur Statistiek gtt Ingenieurwissenschaften Statistik Engineering Statistical methods Physik (DE-588)4045956-1 gnd rswk-swf Statistik (DE-588)4056995-0 gnd rswk-swf Ingenieurwissenschaften (DE-588)4137304-2 gnd rswk-swf Statistik (DE-588)4056995-0 s Ingenieurwissenschaften (DE-588)4137304-2 s DE-604 Physik (DE-588)4045956-1 s Lieberman, Gerald J. 1925- Verfasser (DE-588)111670195 aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001897615&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bowker, Albert H. Lieberman, Gerald J. 1925- Engineering statistics Ingénierie - Méthodes statistiques Mathématiques de l'ingénieur Statistiek gtt Ingenieurwissenschaften Statistik Engineering Statistical methods Physik (DE-588)4045956-1 gnd Statistik (DE-588)4056995-0 gnd Ingenieurwissenschaften (DE-588)4137304-2 gnd |
| subject_GND | (DE-588)4045956-1 (DE-588)4056995-0 (DE-588)4137304-2 |
| title | Engineering statistics |
| title_auth | Engineering statistics |
| title_exact_search | Engineering statistics |
| title_full | Engineering statistics Albert H. Bowker ; Gerald J. Lieberman* |
| title_fullStr | Engineering statistics Albert H. Bowker ; Gerald J. Lieberman* |
| title_full_unstemmed | Engineering statistics Albert H. Bowker ; Gerald J. Lieberman* |
| title_short | Engineering statistics |
| title_sort | engineering statistics |
| topic | Ingénierie - Méthodes statistiques Mathématiques de l'ingénieur Statistiek gtt Ingenieurwissenschaften Statistik Engineering Statistical methods Physik (DE-588)4045956-1 gnd Statistik (DE-588)4056995-0 gnd Ingenieurwissenschaften (DE-588)4137304-2 gnd |
| topic_facet | Ingénierie - Méthodes statistiques Mathématiques de l'ingénieur Statistiek Ingenieurwissenschaften Statistik Engineering Statistical methods Physik |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=001897615&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT bowkeralberth engineeringstatistics AT liebermangeraldj engineeringstatistics |