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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.1 Chapter 13: Sampling: Quantitative and Qualitative

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.2 Contents Samples and populations Representativeness Sample size Weighting Sampling for qualitative research

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.3 Samples and populations Population: –Total category of subjects that is the focus of attention in a particular research project (can be non-human) Sample: –A number of subjects drawn from the population Two key issues: 1.What procedures must be followed to ensure that the sample is representative of the population? 2.How large should the sample be?

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.4 Representativeness Achieved by Random sampling A systematic selection process which ensures that all members of the population have an equal chance of inclusion in the sample Designed to ensure representativeness An unrepresentative sample is: biased How is random sampling achieved in practice?

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.5 Sampling for household surveys Ideally –E.g. 40 million population – sample of 1000: all 40 million names put in a drum and 1000 drawn In practice: –For national/regional surveys – multi-stage sampling used 1.Select states/regions 2.Within state/region select local government area (lga) or constituencies/electorates 3.Within lgas or constituencies/electorates for face-to-face interviews select streets (telephone surveys select numbers at this point) 4.Select clusters of 10–15 houses

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.6 Sampling for telephone surveys Telephone numbers selected at random from telephone directory For large-scale surveys: automated by Computer- Aided telephone Interviewing (CATI) Requires access to electronic directory with residential/business numbers identified No directories for mobile phones For household and telephone surveys: select person in household randomly: e.g. person with next birthday

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.7 Sampling for site/user/visitor surveys Alternative 1: Stationary interviewer - mobile user: –E.g. interviewing at entrance/exit –Sample by selecting: next person to pass entrance/exit point Alternative 2: Stationary user - mobile interviewer –E.g. interviewing people on a beach –Interviewers should have a set route/rules to follow – e.g. interview every third person/group Alternative 3: Handouts –Handing out questionnaires to (all) visitors for self-completion –Not generally recommended unless closely supervised – generally very poor response rates

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.8 Sampling for street/quota surveys Can be used when data are available on key characteristics of population: –Age/sex structure of a community – from Census Interviewing target numbers determined by population characteristics –E.g. If Population Census indicates 12% retired: if overall sample size is 100: interview 12 retired people

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.9 Sampling for mail surveys Sample from mail-out list 100% sample often used

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.10 Sampling for complex events and destination surveys Different components will conform to above guidelines – mostly site surveys Problem lies in combining data from different sources for an overall result, if required

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.11 Sample size Required sample size is not related to population size (except for small populations – see later) Criteria: – The required level of precision in the results – The level of detail in the proposed analysis – The available budget

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.12 Level of precision – confidence intervals A statistic (finding) from a sample survey is an estimate of the population statistic In a randomly drawn sample the sample value has a certain probability of being in a certain range either side of the population value –E.g. 95% probability of being within 2 standard errors See Normal distribution –Theoretical: imagine drawing lots of samples: some would be accurate, some not –Discussed further in Chapter 17

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.13 Figure 13.1 Normal curve

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.14 Sample size (N) Percentages found from sample (results) 50%40/60%30/70%20/80%10/90%5/95%2/98%1/99% Confidence intervals (CIs) ± % 500± 4.4± 4.3± 4.0± 3.5± 2.6± 1.9± 1.2± 0.9 So CI for 20% finding is 30% ±4.0 = a range of: 26.0% – 34.0% CI is not related to population size NB. CI for p = CI for 100-p – e.g. CI is the same for 40% and 60% CI for 50% is the largest in absolute terms This table refers to 95% probability CIs – others can be calculated – e.g. 99% Table 13.1 Confidence intervals (CIs)

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.15 Sample size (N) Percentages found from sample (results) 50%40/60%30/70%20/80%10/90%5/95%2/98%1/99% Confidence intervals (CIs) ± % 500± 4.4± 4.3± 4.0± 3.5± 2.6± 1.9± 1.2± 0.9 2000± 2.2± 2.1± 2.0± 1.7± 1.3± 1.0± 0.6± 0.4 So to halve the CI it is necessary to increase the sample fourfold Table 13.1 Confidence intervals (CIs) (Continued)

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.16 Table 13.1 can be changed to present necessary sample size for a given CI – see Table 13.2 Percentages found from sample (results) Conf. Interval 50%40/60%30/70%20/80%10/90%5/95%1/99% Necessary sample sizes +1+1960092168064614434561824380 +2+22400230420161536864456* +4+4600576504384216114* +8+81501441269653** Table 13.2 Necessary sample sizes to achieve given confidence intervals

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.17 Suggested appendix on sample size and CIs See Appendix 13.1 Table indicating levels of CIs Statement indicating that they have been taken into account

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.18 Detail of proposed analysis Sample size %CIRange, %Comment Survey with sample of 200 200Bowling20+5.514.5 – 25.5Ranges overlap Tennis30+6.323.7 – 36.3 Survey with sample of 500 500Bowling20+3.516.5 – 23.5Ranges do not overlap Tennis30+4.026.0 – 34.0

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.19 Budget Key issue: halving the CI requires 4-fold increase in sample size –E.g. N = 250 CI for 50% = ±6.2 Survey Cost = 200 ×$20 = $5000 N = 1000 CI for 50% = ±3.1 Survey Cost = 1000 × $20 = $20,000 If resources not available for adequate sample size, consider: –Pilot/exploratory study –Qualitative study

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.20 Confidence intervals applied to population estimates Example: Survey with sample 1000 Findings: 12% visit a national park, on average 2.5 times a year CI for 12% of a sample of 1000 is ±2%: range; 10 –14% Population is 500,000 No. of people visiting = 12% of 500,000 = 60,000 At 2.5 times a year = 150,000 visits What is the CI? ±2% of 150,000 = ±3000? NO CI % applies to the population i.e. ±2% of 500,000 = ±10,000 persons With 2.5 visits per person pa = ±25,000 visits to have a CI of ±2% of visits would require a sample size of 75,000

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.21 Sampling for small populations CIs are affected by population size if population is below about 50,000 See Table 13.3

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.22 Table 13.3 Sample size and population size: small populations Population sizeMinimum sample size to achieve CI of ±5% or ±1% on a sample finding of 50% ±5%±1% Infinite3849602 5 million3849584 1 million3849511 500,0003849422 100,0003838761 50,0003818056 10,0003704899 50003573288 1000278906 1008099

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.23 Time# of Interviews%Actual # of users (counts) % 9–11 am1022.2255.7 11.01–1 pm1226.724055.2 1.01–3 pm1124.411025.3 3.01–5 pm1226.7602.7 Total45100.0435100.0 Sample does not reflect the pattern of use Example: one survey at a site Table 13.4 Interview/usage data from a site/visitor survey

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.24 Table 13.5 Weighting ABCD TimeNo. of Interviews No. of Users Weighting Factors Weighted Sample No. Source:SurveyCountsB/ACxA 9–11 am10252.525 11.01–1 pm1224020.0240 1.01–3 pm1111010.0110 3.01–5pm12605.060 Total45435435

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.25 Sampling for qualitative research Number of subjects generally be small, but: –sampling process is still important –should be fully described in research report A range of approaches is possible

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Tony Veal, Research Methods in Leisure and Tourism, 4 th Edition © Pearson Education Limited 2011 Slide 13.26 MethodCharacteristics ConvenienceConveniently located persons or organisations - CriterionSelected on key criterion – e.g. age-group. HomogeneousDeliberately homogeneous group: e.g. university- educated male cyclists aged 20–30. OpportunisticTaking advantages of opportunities as they arise – e.g. a major sporting event taking place locally. Maximum variationDeliberately studying contrasting cases. Opposite of homogeneous. PurposefulSimilar to criterion but may involve other considerations, such as maximum variation, typicality. SnowballInterviewees source of suggestions for contacts. Stratified purposefulA range of cases based on set criteria, e.g. representatives of a range of age-groups or nationalities. Figure 13.2 Sampling for qualitative research

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