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OUTLINE

- Terminology - Difference between Probability sample AND Non-probability sample- How to select sample - Probability sample- Questions

TERMINOLOGY

• Population … is the total collection of elements about which we wish to make some inferences

• Sample … Subset of a larger population• Sampling Frame … is the listing of all population elements from which the

sample will be drawn• Sampling Units … Group selected for the sample• Sampling scheme … Method of selecting sampling units from sampling

frame

GOOD SAMPLE

Good sample depends on the nature of population , time and money - The sample must be:

1. representative of the population2. appropriately sized (the larger the better)3. unbiased4. random (selections occur by chance)

SAMPLING TECHNIQUE

DIFFERENCE BETWEEN …

• Probability sample – a method of sampling that uses of random selection so that all units/ cases in the population have an equal probability of being chosen.

• Non-probability sample – does not involve random selection and methods are not based on the rationale of probability theory.

SIMPLE RANDOM SAMPLING

• A sampling procedure that ensures that each element in the population will have an equal chance of being included in the sample

Advantages• Easy to implement with random dialingDisadvantages• Requires list of population elements• Time consuming• Larger sample needed• Produces larger errors• High cost

SYSTEMATIC SAMPLING • A simple process , Every name from the list will be drawn and systematically chose

sample Advantages• Simple to design• Easier than simple random• Easy to determine sampling distribution of mean or proportionDisadvantages• Trends in list may bias results• Moderate cost

STRATIFIED SAMPLING

• Subsamples are drawn within different strata • Each stratum is more or less equal on some characteristicAdvantages• Control of sample size in strata• Increased statistical efficiency• Provides data to represent and analyze subgroups• Enables use of different methods in strataDisadvantages• Increased error if subgroups are selected at different rates• Especially expensive if strata on population must be created • High cost

CLUSTER SAMPLINGthe researcher divides the population into separate groups, called clusters then, a simple random sample of clusters is selected from the population. The researcher conducts his analysis on data from the sampled clusters• Advantages• Provides an unbiased • Economically more efficient than simple random• Lowest cost per sample• Easy to do without listDisadvantages• Often lower statistical efficiency due to subgroups being homogeneous rather than heterogeneous• Moderate cost

SIMPLE RANDOM SAMPLING

SYSTEMATIC SAMPLING

STRATIFIED SAMPLING

CLUSTER SAMPLING

REFERENCE

• https://www.mathstopia.net/sampling/systematic-random-sampling• https://en.wikipedia.org/wiki/Sampling_(statistics)• http://www.simplypsychology.org/sampling.html