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Data collection (Sampling (• Simple random sample of size n is where…
Data collection
Populations and samples
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• Disadvantages of census: Time consuming and expensive, cannot be used when testing process destroys item, hard to process large quantity of data
• Advantages of sample: less time consuming and expensive, fewer people have to respond and less data to process than in census
• Disadvantages of sample: data may not be as accurate, sample may not be large enough to give information about smaller sub-groups of the population
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Sampling
• Simple random sample of size n is where every sample of size n has an equal chance of being selected
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• In stratified sampling the population is divided into mutually exclusive strata (eg. genders) and a random sample is taken from each
• Number of people sampled in a stratum is (number in stratum) / (number in population) × overall sample size
• Advantages simple random: free of bias, cheap and easy, each sample unit same chance of selection
• Disadvantages simple random: not suitable when population size or sample size is large, sampling frame needed
• Advantages systematic: simple and quick, suitable for large populations and samples
• Disadvantages systematic sampling frame needed, can introduce bias if sampling frame not random
• Advantages stratified: sample accurately reflects population structure, guarantees proportional representation
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Non-random sampling
• Quota sampling: interviewer or researcher selects sample which reflects characteristics of whole population
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• Advantages quota: allows small sample to be representative of population, no sampling frame needed, quick, cheap, easy and allows for easy comparison between different groups within a population
• Disadvantages quota: can introduce bias, needed distinct groups, higher scope of study = more groups
• Advantages opportunity: easy to carry out, inexpensive
• Disadvantages opportunity: unlikely to provide representative sample, highly dependent on individual researcher
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