Russel-Research-Method-in-Anthropology

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168 Chapter 6 have only 15 people in each of the eight conditions, then you need a sample of 120. The same principle holds when you’re trying to figure out how big a sample you need for a survey. In the example above about stratified random sampling, we had four generations and two genders—which also produced an eight-cell design. If all you want to know is a single proportion—like what percentage of people in a population approve or disapprove of something—then you need about 100 respondents to be 95% confident, within plus or minus 3 points, that your sample estimate is within 2 standard deviations of the population parameter (more about confidence limits, normal distributions, standard deviations, and parameters coming next). But if you want to know whether women factory workers in Rio de Janeiro who earn less than $300 per month have different opinions from, say, middle-class women in Rio whose family income is more than $600 per month, then you’ll need a bigger sample. 3. The size of the subgroup. If the population you are trying to study is rare and hard to find, and if you have to rely on a simple random sample of the entire population, you’ll need a very large initial sample. A needs assessment survey of people over 75 in Florida took 72,000 phone calls to get 1,647 interviews— about 44 calls per interview (Henry 1990:88). This is because only 6.5% of Florida’s population was over 75 at the time of the survey. By contrast, the monthly Florida survey of 600 representative consumers takes about 5,000 calls (about eight per interview). That’s because just about everyone in the state 18 and older is a consumer and is eligible for the survey. (Christopher McCarty, personal communication) The smaller the difference on any measure between two populations, the bigger the sample you need in order to detect that difference. Suppose you suspect that Blacks and Whites in a prison system have received different sentences for the same crime. Henry (1990:121) shows that a difference of 16 months in sentence length for the same crime would be detected with a sample of just 30 in each racial group (if the members of the sample were selected randomly, of course). To detect a difference of 3 months, however, you need 775 in each group. 4. Precision. This one takes us into sampling theory.
7 ◆ Sampling Theory Distributions At the end of this chapter, you should understand why it’s possible to estimate very accurately, most of the time, the average age of the 213 million adults in the United States by talking to just 1,600 of them. And you should understand why you can also do this pretty accurately, much of the time, by talking to just 400 people. Sampling theory is partly about distributions, which come in a variety of shapes. Figure 7.1 shows what is known as the normal distribution 34.13% 34.13% 13.59% 13.59% 2.14% 2.14% -3 SD -2 SD -1 SD x +1 SD +2 SD +3 SD mean -1.96 +1.96 Figure 7.1. The normal curve and the first, second, and third standard deviation. 169
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H. Russell Bernard FOURTH EDITION R
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Research Methods in Anthropology Fo
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Contents Preface vii 1. Anthropolog
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Preface Since 1988, when I wrote th
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Preface ix sampling: why we do it a
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Preface xi 21, you will be able to
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Preface xiii testimony. There is an
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Preface xv begin writing the second
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1 ◆ Anthropology and the Social S
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Anthropology and the Social Science
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The Foundations of Social Research
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3 ◆ Preparing for Research Settin
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Preparing for Research 71 research
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Preparing for Research 73 morning u
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Preparing for Research 75 the AAA b
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Preparing for Research 77 showed wh
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Preparing for Research 79 That will
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Preparing for Research 81 mothers.
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Preparing for Research 83 gathering
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Preparing for Research 85 hypothesi
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Preparing for Research 87 I mention
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Preparing for Research 89 A Guide t
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Preparing for Research 91 people re
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Preparing for Research 93 Observed
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Preparing for Research 95 dent. (Re
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The Literature Search 97 too busy t
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The Literature Search 99 year, who
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The Literature Search 101 like demo
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The Literature Search 103 reports e
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The Literature Search 105 gists, in
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The Literature Search 107 Women Sca
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5 ◆ Research Design: Experiments
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Research Design: Experiments and Ex
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Page 135 and 136: Research Design: Experiments and Ex
Page 165 and 166: Sampling 147 ried around here deliv
Page 167 and 168: Sampling 149 the potential sampling
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Page 171 and 172: Sampling 153 116. If the first rand
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Page 177 and 178: Sampling 159 Probability Proportion
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Page 181 and 182: Sampling 163 the cluster, the large
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Page 197 and 198: Sampling Theory 179 Calculating Sam
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Page 201 and 202: Sampling Theory 183 and we solve fo
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Page 205 and 206: Nonprobability Sampling and Choosin
Page 223 and 224: TABLE 8.4 Matches, Proportions of M
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Interviewing: Unstructured and Semi
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10 ◆ Structured Interviewing I: Q
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Structured Interviewing I: Question
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11 ◆ Structured Interviewing II:
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Structured Interviewing II: Cultura
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Scales and Scaling 319 10 times, or
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Scales and Scaling 321 students’
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Scales and Scaling 323 points. The
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Scales and Scaling 325 TABLE 12.2a
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Scales and Scaling 327 wealth in vi
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Scales and Scaling 329 You may obse
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Scales and Scaling 331 interitem co
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Scales and Scaling 333 ality of a s
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Scales and Scaling 335 TABLE 12.7 T
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Scales and Scaling 337 Having a Col
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Scales and Scaling 339 The Cantril
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Scales and Scaling 341 and has been
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Participant Observation 343 Romanci
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Participant Observation 345 sion, s
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Participant Observation 347 doses o
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Participant Observation 349 great s
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Participant Observation 351 less—
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Participant Observation 353 oped by
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Participant Observation 355 Graham
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Participant Observation 357 ters fr
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Participant Observation 359 washing
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Participant Observation 361 that yo
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Participant Observation 363 ‘‘c
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Participant Observation 365 hall wh
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Participant Observation 367 Maintai
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Participant Observation 369 not to
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Participant Observation 371 pletely
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Participant Observation 373 changed
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Participant Observation 375 Besides
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Participant Observation 377 Thomas
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Participant Observation 379 But not
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Participant Observation 381 baby’
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Participant Observation 383 into fo
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Participant Observation 385 in Mace
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14 ◆ Field Notes: How to Take The
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Field Notes: How to Take Them, Code
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15 ◆ Direct and Indirect Observat
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Direct and Indirect Observation 415
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16 ◆ Introduction to Qualitative
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Introduction to Qualitative and Qua
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START: SEARCH WHOLESALE MARKET FOR
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17 ◆ Qualitative Data Analysis I:
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Qualitative Data Analysis I: Text A
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Qualitative Data Analysis II: Model
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19 ◆ Univariate Analysis The next
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Univariate Analysis 551 But if you
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Univariate Analysis 553 TABLE 19.1
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Univariate Analysis 555 Notice in t
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Univariate Analysis 559 TABLE 19.3b
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Univariate Analysis 561 possible an
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Univariate Analysis 563 people hang
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Univariate Analysis 573 Number of C
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Univariate Analysis 575 some basic
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Univariate Analysis 577 interquarti
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Univariate Analysis 579 countries t
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Univariate Analysis 581 Both groups
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Univariate Analysis 585 would be no
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Univariate Analysis 587 rejecting H
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Univariate Analysis 589 lation, 68.
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Univariate Analysis 591 of Shipibo
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TABLE 19.13 Chi-Square for a Univar
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Bivariate Analysis: Testing Relatio
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TABLE 20.20 Correlation Matrix of A
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21 ◆ Multivariate Analysis Most o
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Multivariate Analysis 651 environme
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Multivariate Analysis 653 TABLE 21.
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TABLE 21.11 Wealth by Education, Co
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Multivariate Analysis 657 it is hig
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Multivariate Analysis 659 ideas abo
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Multivariate Analysis 661 You can a
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Multivariate Analysis 663 which mea
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Multivariate Analysis 667 In fact,
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Multivariate Analysis 669 under plo
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Multivariate Analysis 671 fr .968 R
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Multivariate Analysis 673 earity pr
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Multivariate Analysis 675 BTU and O
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Multivariate Analysis 677 Factor An
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Multivariate Analysis 679 columns h
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Multivariate Analysis 681 4. Across
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Multivariate Analysis 683 instead o
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Multivariate Analysis 687 1.71 1.32
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Multivariate Analysis 689 ‘‘chi
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Multivariate Analysis 691 6, 1, 4.
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Multivariate Analysis 693 Lambros C
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Multivariate Analysis 695 just beca
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698 Appendix A 32179 00597 87379 25
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APPENDIX B Table of Areas under a N
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702 Appendix B (A) (B) (C) (A) (B)
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APPENDIX D Chi-Square Distribution
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APPENDIX E F Table for the .05 Leve
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708 Appendix E F Table for the .01
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APPENDIX F Resources for Fieldworke
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712 References obesity in Saudi Ara
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714 References Beautrais, A. L., P.
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716 References the self-assessment
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718 References Bradburn, N. M. 1983
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720 References ments by considering
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722 References ing in reflected glo
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724 References village. In Self, se
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726 References Duncan, O. D. 1966.
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728 References achieve high respons
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730 References Gatz, M., and M. Hur
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732 References C2KBR/01-1. Washingt
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734 References study of relationshi
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736 References Hornik, J., and S. E
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738 References esses in survey rese
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740 References Kessler, R. C., and
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742 References Laban Moogi Gwako, E
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744 References Lewis, R. B. 2004. N
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746 References McCall, G. 1978. Obs
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748 References Morgan, D. L. 1997.
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750 References Oakhill, J., and A.
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752 References Piliavin, I. M., J.
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754 References nicity-of-interviewe
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756 References Rotton, J., and M. S
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758 References Schwarts, N. A. 2004
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760 References Smith, L. D. 1986. B
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762 References Stricker, L. J. 1988
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764 References pharmacists in HIV/S
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766 References Webb, E. J., D. T. C
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768 References Williams, T. 1996. E
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Subject Index Numbers in italics re
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Subject Index 773 Campos, Alberto,
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Subject Index 775 data analysis, 45
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Subject Index 777 external states,
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Subject Index 779 individual attrib
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Subject Index 781 median, 562, 563-
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Subject Index 783 parsimony, princi
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Subject Index 785 random digit dial
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Subject Index 787 simple scales, 31
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Subject Index 789 T-scores, 591 t-t
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Author Index Numbers in italics ref
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Author Index 793 Choi, N., 33 Choms
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Author Index 795 Gregson, S., 93 Gr
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Author Index 797 Leap, W., 376 LeCo
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Author Index 799 Rashid, R. G., 121
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Author Index 801 Vadez, V., 55, 93
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