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Marketing Research - Sampling (Types of Sampling (Cluster sampling (A…
Marketing Research - Sampling
Sample Design
Sample structure.
Plans for analysing and interpreting the results. :
Method of selection.
Defining the Population
The second is to use the sampling frame to sample the target population.
Third, units in the population can be identified by existing information (e.g., payroll, company lists, government registers, etc.).
The first step is to ensure that the target audience's specifications are as clear and complete as possible.
The fourth is that the sampling framework can also be geographic
Sample Size
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
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 sample
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
Types of Sampling
Cluster sampling
A random sample of clusters is taken, then all units within the cluster are examined.
Advantages
Doesn't need complete population information
Good for face-to-face surveys
Quick and easy
Disadvantages
Expensive if the clusters are large
Greater risk of sampling error
Convenience sampling
Uses those who are willing to volunteer and easiest to involve in the study.
Advantages
Subjects are readily available
Large amounts of information can be gathered quickly
Disadvantages
The sample is not representative of the entire population, so results can't speak for them - inferences are limited. future data
Prone to volunteer bias
Judgement sampling
A deliberate choice of a sample - the opposite of random
Advantages
Good for providing illustrative examples or case studies
Disadvantages
Very prone to bias
Samples often small
Cannot extrapolate from sample
Quota sampling
The aim is to obtain a sample that is "representative" of the overall population.
Advantages
Quick and easy way of obtaining a sample
Disadvantages
Not random, so some risk of bias
Need to understand the population to be able to identify the basis of stratification
Simply random sampling
This makes sure that every member of the population has an equal chance of selection
Advantages
Simple to design and interpret
Can calculate both estimate of the population and sampling error
Disadvantages
Need a complete and accurate population listing
May not be practical if the sample requires lots of small visits over the country
Systematic sampling
After randomly selecting a starting point from the population between 1 and *n, every nth unit is selected.
Advantages
Easier to extract the sample than via simple random
Ensures sample is spread across the population
Disadvantages
Can be costly and time-consuming if the sample is not conveniently located