Sampling methods for applied research: text and cases
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Wiley
1996
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XI, 440 S. graph. Darst. |
| ISBN: | 0471047279 |
Internformat
MARC
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| 245 | 1 | 0 | |a Sampling methods for applied research |b text and cases |c Peter Tryfos |
| 264 | 1 | |a New York [u.a.] |b Wiley |c 1996 | |
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Datensatz im Suchindex
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| adam_text | Titel: Sampling methods for applied research
Autor: Tryfos, Peter
Jahr: 1996
CONTENTS
PART ONE: TEXT
Chapter 1 Introduction 3
1.1 Sampling the issues 3
1.2 Case: Print Media Research 4
1.3 Case: Telemedia Inc. 6
1.4 Case: Norpower Inc. 7
1.5 Case: Pharmacom Research 9
1.6 Case: Canabag Manufacturing Company 11
1.7 Some reflections 12
1.8 A very brief history of sampling 14
1.9 A disclaimer 15
Chapter 2 Preliminaries
16
2.1 Introduction and summary 16
2.2 Populations and their characteristics 17
2.3 Proportions and indicator variables 23
2.4 First assumptions 24
2.5 First estimates 24
2.6 Sampling with and without replacement 25
2.7 Is a larger sample better? 26
2.8 Sampling from a homogeneous
population 28
2.9 Auxiliary information 29
2.10 Sampling from homogeneous groups 30
2.11 Sampling of groups 32
2.12 Exploiting a relationship 35
2.13 A note on terminology 39
2.14 To sum up 40
Chapter 3 Simple random sampling 41
3.1 Introduction and summary 41
3.2 A silly game 42
3.3 Simple random samples 45
3.4 The Ackroyd population 47
3.5 Implications 54
3.6 Selecting a random sample in practice 58
3.7 How large should a sample be? 60
3.8 Interval estimates 66
3.9 To sum up 70
Problems 71
Chapter 4 Stratified random
sampling
4.1 Introduction and summary 84
4.2 Stratified sampling?a first view 85
84
Contents
4.3 The Ackroyd case continued 88
4.4 Properties of stratified estimators 94
4.5 Proportional stratified sampling 96
4.6 Optimal stratified sampling 99
4.7 How large a stratified sample? 104
4.8 Interval estimates 105
4.9 To sum up 107
Problems 108
6.12
Chapter 5
Two-stage random
sampling
120
5.1 Introduction and summary 120
5.2 Some advantages of two-stage
sampling 121
5.3 Properties of two-stage estimators 126
5.4 Special case: cluster sampling 131
5.5 Special case: systematic sampling 133
5.6 Stratified or two-stage sampling? 136
5.7 Interval estimates 139
5.8 Combined stratified/two-stage
sampling 142
5.9 Multistage sampling 144
5.10 To sum up 145
Problems 146
Chapter 6 Ratio and regression
estimators 156
6.1 Introduction and summary 136
6.2 A simple linear relationship 157
6.3 Ratio estimators and modified simple random
sampling 161
6.4 Properties of the ratio estimator 162
6.5 The regression estimator 165
6.6 Properties of the regression estimator 168
6.7 Ratio and regression estimators in large
samples 171
6.8 Sample size 176
6.9 Interval estimates 177
6.10 Regression and ratio estimators in stratified
sampling 180
6.11 Regression and ratio estimators in two-stage
sampling 183
To sum up 185
Problems 185
Chapter 7 Some special topics
195
7.1 Introduction and summary 195
7.2 Estimating the ratio of totals or means of two
variables 196
7.3 Estimating subpopulation means and
proportions 199
7.4 Cluster sampling?an alternative view 207
7.5 Poststratification 209
7.6 Double sampling 212
7.7 To sum up 215
Problems 216
Chapter 8 Sampling with unequal
probabilities
225
8.1 Introduction and summary 225
8.2 Inclusion probabilities 226
8.3 The Horvitz-Thompson estimator
(HTE) 227
8.4 Application: Three-stage sampling 231
8.5 The variance of the HTE and
implications 234
8.6 Inclusion probabilities proportional to size
(IPPS) 237
8.7 Sampling with IPPS 240
8.8 Some observations on the HTE 242
8.9 Interval estimates based on the HTE 243
8.10 Sampling with replacement and PPS 245
8.11 Interval estimates based on the HHE 250
8.12 Application: Dollar-unit sampling 252
8.13 To sum up 255
Problems 256
Chapter 9 Sampling from a process
266
9.1 Introduction and summary 266
9.2 The prediction approach 267
9.3 A simple linear model with no intercept 270
9.4 Best linear unbiased estimator
confirmed 275
Contents
xl
9.5 Some variants of the sample linear model
with no intercept 279
9.6 Interval estimates, simple linear models with
no intercept 281
9.7 A simple linear model with intercept 283
9.8 A linear model with more than one
explanatory variable 287
9.9 The prediction approach in general 292
9.10 Simple diagnostic tools 292
9.11 Prediction vs. randomization 294
Problems 295
PART TWO: CASES___________
Chapter 10 Nonsampling errors
307
10.1 Introduction and summary 307
10.2 Entire population available 308
10.3 Identifying the population elements 309
10.4 Case: Telephone surveys 311
10.5 Nonresponse 313
10.6 Measurement error 315
10.7 Randomized response 317
10.8 Case: Radio and television
measurement 320
10.9 To sum up 324
Problems 327
Canabag Manufacturing Company?Part I 335
Canabag Manufacturing Company?Part II 340
Valuation of government properties?Part I 343
Valuation of government properties?Part II 345
Valuation of government properties?Part III 353
Valuation of government properties?Part IV 355
PackGoods Inc. 356
Pharmacom Research?Part I 364
Pharmacom Research?Part II 374
Tenderdent Toothpaste 483
APPENDICES
Appendix A Bask concepts
A.1 The summation notation 391
A.2 Distributions 393
A.3 Measures of central tendency and
dispersion 395
A.4 Probability 399
A.5 Probability distributions 400
A.6 Correlation 402
A.7 Least squares estimation 406
A.8 A note on variances and covariances
391
Appendix B
Glossary and technical
summary
408
410
B.l Notation 410
B.2 Simple random sampling (chapter 3) 413
B.3 Stratified random sampling (chapter 4) 414
B.4 Two-stage random sampling (chapter 5)
416
B.5 Ratio and regression estimators (chapter 6)
417
B.6 Some special topics (chapter 7) 419
B.7 Sampling without replacement and unequal
probabilities (chapter 8) 420
B.8 Sampling with replacement and unequal
probabilities (chapter 8) 422
B.9 Sampling from a process (chapter 9) 423
Appendix C Computing Instructions 426
C.l General 426
C.2 The Canabag program 427
C.3 The SCALC program 428
Appendix D Solutions to selected
problems 432
Bibliography 434
Index 437
|
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| language | English |
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| spelling | Tryfos, Peter Verfasser aut Sampling methods for applied research text and cases Peter Tryfos New York [u.a.] Wiley 1996 XI, 440 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Amostragem (estatistica) larpcal Estatistica aplicada as ciencias exatas larpcal Steekproeven gtt Sampling (Statistics) Stichprobe (DE-588)4057502-0 gnd rswk-swf Angewandte Forschung (DE-588)4142434-7 gnd rswk-swf Stichprobe (DE-588)4057502-0 s Angewandte Forschung (DE-588)4142434-7 s DE-604 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=007221910&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Tryfos, Peter Sampling methods for applied research text and cases Amostragem (estatistica) larpcal Estatistica aplicada as ciencias exatas larpcal Steekproeven gtt Sampling (Statistics) Stichprobe (DE-588)4057502-0 gnd Angewandte Forschung (DE-588)4142434-7 gnd |
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| title | Sampling methods for applied research text and cases |
| title_auth | Sampling methods for applied research text and cases |
| title_exact_search | Sampling methods for applied research text and cases |
| title_full | Sampling methods for applied research text and cases Peter Tryfos |
| title_fullStr | Sampling methods for applied research text and cases Peter Tryfos |
| title_full_unstemmed | Sampling methods for applied research text and cases Peter Tryfos |
| title_short | Sampling methods for applied research |
| title_sort | sampling methods for applied research text and cases |
| title_sub | text and cases |
| topic | Amostragem (estatistica) larpcal Estatistica aplicada as ciencias exatas larpcal Steekproeven gtt Sampling (Statistics) Stichprobe (DE-588)4057502-0 gnd Angewandte Forschung (DE-588)4142434-7 gnd |
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