Slide 10.1 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Chapter 10: Sampling

Slide 10.2 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Contents I. Samples and populations II. Representativeness – random sampling III. Sample size IV. Weighting V. Sampling for qualitative research.

Slide 10.3 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 A. 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?

Slide 10.4 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 B. Representativeness  Achieved by random sampling: A selection process which ensures that all members of the population have an equal chance of inclusion in the sample Systematic Designed to ensure representativeness  An unrepresentative sample is: biased  How is random sampling achieved in practice?

Slide 10.5 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Random sampling in household surveys  Ideally For example, 10 million population – sample of 1000: all 10 m 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 areas (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.

Slide 10.6 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Random sampling in site/user/visitor surveys  Alternative 1: Stationary interviewer – mobile user: For example, interviewing at entrance/exit Sample by selecting: ‘next person to pass entrance/exit point’  Alternative 2: Stationary user – mobile interviewer For example, interviewing people on a beach Interviewers should have a set route/rules to follow – for example, ‘interview every third person/group’  Alternative 3: Handouts Handing out questionnaires to customers etc. for self- completion Not generally recommended unless closely supervised – generally very poor response rates.

Slide 10.7 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Sampling for street surveys – quota sampling  Can be used when data are available on key characteristics of population: Age structure/sex ratio of users – from membership records Age/sex structure of a community – from census  Interviewing target numbers determined by population characteristics For example, if population census indicates 12% retired and if overall sample size is 200 then interview 24 retired people.

Slide 10.8 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Sampling for mail surveys  Sample from mail-out list  100% sample often used.

Slide 10.9 Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 C. Sample size  Required sample size is not related to population size (except for small populations – see slides & 10.23)  See – political opinion polls.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Opinion polls and sample size Error (Confidence intervals) Voting intentions % +0.9%2%Nader/Camejo 3.1% +3.1%45%Kerry/Edwards 3.1% +3.1%48%Bush/Cheney USA – Sept ’04 – NBC/WSJ – voters 156 m – sample size 1006

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Error (Confidence intervals) Voting intentions % +1.4%6%Greens 3.0% +3.0%42%Labour 3.0% +3.0%39%Liberal/National Australia – Aug ’04 – Newspoll – voters 13 m – sample size 1047 % +0.9%2%Nader/Camejo 3.1% +3.1%45%Kerry/Edwards 3.1% +3.1%48%Bush/Cheney USA – Sept ’04 – registered voters 156 m – sample size 1006 Sample sizes and margins of error are similar, despite great difference in population. Opinion polls and sample size (contd.)

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Determinants of sample size 1. The required level of precision in the results 2. The level of detail in the proposed analysis 3. The available budget.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited Precision – confidence intervals  A statistic (finding) from a sample 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 on either side of the population value For example, 95% probability of being within two ‘standard errors’  See normal distribution – Fig. 10.1

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Precision - confidence intervals normal curve(Fig. 10.1)

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Confidence intervals and sample size – Table 10.1 So CI for 20% finding is 30% ± 4.0 = a range of 26.0% to 34.0%. CI is not related to population size. NB.  CI for p = CI for 100−p  CI for 50% is the largest in absolute terms  This table refers to 95% probability CIs – other probabilities can be calculated – for example, 99%. Confidence intervals (CIs) (+ %) or 99% 2 or 98% 5 or 95% 10 or 90% 20 or 80% 30 or 70% 40 or 60% 50% Percentages found from sample (‘results’)Sample size (N)

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Confidence intervals and sample size – Table 10.1 (contd.) Confidence intervals (CIs) (+ %) or 99% 2 or 98% 5 or 95% 10 or 90% 20 or 80% 30 or 70% 40 or 60% 50% Percentages found from sample (‘results’)Sample size (N) So, to halve the CI it is necessary to increase the sample fourfold.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Confidence intervals and sample size Table 10.1 can be changed to present necessary sample size for a given CI – see Table 10.2 ** % * % * ,5362,0162,3042,400+2% 3801,8243,4566,1448,0649,2169,600+1% Necessary sample sizes 1 or 99% 5 or 95% 10 or 90% 20 or 80% 30 or 70% 40 or 60% 50%Conf. interval Percentages found from sample (‘results’)

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited Sample size – level of detail of analysis 23.7 – – 25.5 Range, % Ranges overlap Comment CI 30Tennis 20Bowling200 %Sampl e size

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited Sample size – level of detail of analysis (contd.) The larger sample allows greater precision – Tennis 16.5 – – – 25.5 Range, % Ranges do not overlap Ranges overlap Comment CI 20Bowling500 30Tennis 20Bowling200 %Sample size

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited Sample size - budget  Key issue: halving the CI requires fourfold increase in sample size For example, N = 250 CI for 50% = +6.2 Survey cost = 200 x $20 = $4,000 N = 1,000 CI for 50% = +3.1 Survey cost = 1,000 x $20 = $20,000  If resources are not available for adequate sample size, consider: Pilot/exploratory study Qualitative study.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Sample size – reporting  Readers of research reports should be alerted to problems of confidence intervals – See Appendix 10.1 for suggested format  Researchers should take account of confidence intervals and indicate when differences are not statistically significant.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Sample size – small populations  CIs are affected by population size if the population is less than 50,000  See Table 10.3.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Sample size small populations – Table %+5% , , ,000 8, , ,761100,000 9,422500,000 9,5111 million 9,5845 million 9,602Infinite Minimum sample size to achieve CI of +5% or +1% on a sample finding of 50% Population size

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 D. Weighting Table 10.4 Interview/usage data from a site/visitor survey

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 D. Weighting Table 10.5 (contd.)

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 E. Sampling and qualitative research  Statistical representativeness not claimed, but  Sample is often claimed to represent wide range of groups/situations  Purposive sampling is often undertaken to ensure wide range

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Types of qualitative sampling – Table 10.6 ConvenienceUse of conveniently located persons or organisations – for example, friends, colleagues, students, organisations in the neighbourhood, tourists visiting a local popular attraction. CriterionIndividuals selected on the basis of a key criterion – for example, age-group, membership of an organisation, purchasers of souvenirs. Homogeneou s Deliberately selecting a relatively homogeneous sub- set of the population – for example, university- educated male cyclists aged 20–30. OpportunisticSimilar to 'convenience' but involves taking advantages of opportunities as they arise – for example, studying major sporting event taking place locally, or a holiday resort the researcher is holidaying at.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Types of qualitative sampling – Table 10.6 (contd.) Maximum variation Deliberately studying contrasting cases. Opposite of 'homogeneous'. PurposefulSimilar to 'criterion' but may involve other considerations, such as 'maximum variation', typicality. Stratified purposeful Selection of a range of cases based on set criteria, for example, representatives of a range of age-groups or nationalities.

Slide Veal, Research Methods for Leisure and Tourism, 3 rd edition © Pearson Education Limited 2006 Summary  A sample is selected from a population.  A sample that is not representative of the population is biased.  Random sampling seeks to provide a representative sample and to minimise bias.  Practical problems of achieving random sampling vary with the type of survey.  Three criteria for determining sample size: the level of precision of results, the level of detail in the proposed analysis, and the budget.  The level of precision of results depends on the confidence intervals (CIs) which vary according to sample size.  Halving the CI requires a fourfold increase in sample size.  When certain characteristics of the population are known (e.g. the age/sex structure), weighting can be used to correct any lack of representativeness in the sample.  In qualitative research, samples are not statistically representative but may aim at a broad representativeness.