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Market Research-Sampling (types of sampling (Judgement sampling (A…
Market Research-Sampling
Sample Design
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The sample design may make use of the characteristics of the overall market population, but it does not have to be proportionally representative.
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Defining the population
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The first step in good sample design is to ensure that the specification of the target population is as clear and complete as possible. This is to ensure that all elements within the population are represented.
sample size
The confidence level is the likelihood that the results obtained from the sample lie within a required precision: the higher the confidence level, the more certain you wish to be that the results are not atypical. Statisticians often use a 95% confidence level to provide strong conclusions
Population size does not normally affect sample size: in fact the larger the population size, the lower the proportion of that population needs to be sampled to be representative. It's only when the proposed sample size is more than 5% of the population that the population size becomes part of the formulae to calculate the sample size
To lower the margin of error usually requires a larger sample size: the amount of variability in the population, ie the range of values or opinions, will also affect accuracy and therefore size of the
No estimate taken from a sample is expected to be exact: assumptions about the overall population based on the results of a sample will have an attached margin of error
types of sampling
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Quota sampling
The aim is to obtain a sample that is "representative" of the overall population. The population is divided ("stratified") by the most important variables such as income, age and location. The required quota sample is then drawn from each stratum.
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Disadvantages: Not random, so some risk of bias. Need to understand the population to be able to identify the basis of stratification
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cluster sampling
Units in the population can often be found in certain geographic groups or "clusters" for example, primary school children in Derbyshire.
A random sample of clusters is taken, then all units within the cluster are examined.
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Advantages: Quick and easy. Doesn't need complete population information. Good for face-to-face surveys
Systematic sampling
After randomly selecting a starting point from the population between 1 and n, every nth unit is selected. n equals the population size divided by the sample size.
Advantages: Easier to extract the sample than via simple random. Ensures sample is spread across the population
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