1. RESEARCH METHODS IN TOURISM Nicos Rodosthenous PhD 18/04/2013 10 25/4/20131Dr Nicos Rodosthenous

2. Develop sample: the idea of sampling; Samples and population; Sample size 1.Introduction  In most survey research and in some observational research it is necessary to sample.  Mainly because of costs, it is not usually possible to gather data from all the people, organizations which are the focus of the research 2. The idea of sampling  For example, to study the leisure patterns or holiday-making behavior of the population of a country. 25/4/20132Dr Nicos Rodosthenous

3. Develop sample: the idea of sampling; Samples and population; Sample size  It would be impossible to conduct face-to-face interviews with millions of individuals in busy periods  To hand respondent-completion questionnaires to all users it may have disadvantages in terms of quality and the level of response.  The usual procedure is to interview a sample-a proportion-of the users  Sampling has implications for the way data are collected, analysed and interpreted. 25/4/20133Dr Nicos Rodosthenous

4. Develop sample: the idea of sampling; Samples and population; Sample size 3. Samples and populations  A sample is selected from the population, i.e. population of Cyprus or London.  In social research, the visitors to a resort constitute the population of resort visitors and the users of a sports facility are the population of users  The term population can also be applied to non- human phenomena, i.e. the study of Cyprus beaches from which 10 were to be selected for study. 25/4/20134Dr Nicos Rodosthenous

5. Develop sample: the idea of sampling; Samples and population; Sample size  The 100 beaches can be referred to as the population of beaches and the 10 selected for study the sample.  In a sample study there are two questions:  1) What procedures must be followed to ensure that the sample is representative of the population?  2) How large should the sample be?  The larger the sample the more chance of being representative. 25/4/20135Dr Nicos Rodosthenous

6. Develop sample: the idea of sampling; Samples and population; Sample size 3.1. Representativeness  A sample which is not representative of the population is described as biased.  The researcher seeks to minimize bias by adopting the principles of random sampling.  In random sampling all members of the population have an equal chance of inclusion in the sample.  For example, if a sample of 1,000 people are selected from a population of 10,000 then 25/4/20136Dr Nicos Rodosthenous

7. Develop sample: the idea of sampling; Samples and population; Sample size  every member has a 1 in 10 chance of being selected. 3.2. Sampling for household surveys  There are published tables for random numbers produced by computers.  Electoral registers are also used and if the proposed sample is 1000, then it would be sub-divided in the various regions, i.e. in Cyprus in 5 regions. 25/4/20137Dr Nicos Rodosthenous

8. Develop sample: the idea of sampling; Samples and population; Sample size 3.3. Sampling for site/user/visitor surveys  Conditions at tourism sites vary, depending on the type and size, the season, day of the week, the time or the weather.  To ensure randomness the interviewer can be stationary and the users mobile or v.v. 3.4. Sampling for street surveys and quota sampling  The street survey is seen as a means of a sample of the community or visitors to an area. 25/4/20138Dr Nicos Rodosthenous

9. Develop sample: the idea of sampling; Samples and population; Sample size  It can also be seen as a sort of ‘site survey’, i.e. shopping or tourist area. 3.5. Sampling for mail surveys  The questionnaire is sent in a mail survey to the whole population or a sample. 4. Sample size  What is important is the absolute size of the sample, regardless of the size of the population. 25/4/20139Dr Nicos Rodosthenous

10. Develop sample: the idea of sampling; Samples and population; Sample size  The criteria of the sample size are:  1) the required level of precision in the results  2) the level of detail in the proposed analysis  3) the available budget 5. Sample size and small populations  The relationship between the size of confidence intervals and the size of the population becomes noticeable when the population size falls below 50,000 25/4/201310Dr Nicos Rodosthenous

11. Develop sample: the idea of sampling; Samples and population; Sample size 25/4/201311Dr Nicos Rodosthenous

12. Develop sample: the idea of sampling; Samples and population; Sample size 6. Weighting  The aim of weighting is to produce a weighted sample with distribution similar to the actual users  The initial weighting factors are equal to the user number divided by the sample number. 25/4/201312Dr Nicos Rodosthenous

13. Develop sample: the idea of sampling; Samples and population; Sample size 25/4/201313Dr Nicos Rodosthenous

14. Develop sample: the idea of sampling; Samples and population; Sample size 25/4/201314Dr Nicos Rodosthenous