Sampling Techniques

-Hareesh M2014600120

Why Sampling..?

• Less Cost• Less Field time• The population of interest is usually too large to

attempt to survey all of its members. • A carefully chosen sample can be used to represent

the population.– The sample reflects the characteristics of the

population from which it is drawn.• Sample described as a representative “taste” of a

group.

Sampling…

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• What is your population of interest?• To whom do you want to generalize your

results?–All doctors–School children– Indians–Women aged 15-45 years–Other

• Can you sample the entire population?

Sampling…..

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• 3 factors that influence sample representative-ness• Sampling procedure• Sample size• Participation (response)

• When might you sample the entire population?• When your population is very small• When you have extensive resources• When you don’t expect a very high response

5SAMPLING BREAKDOWN

Process

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• The sampling process comprises several stages:– Defining the population of concern – Specifying a sampling frame, a set of items or events

possible to measure – Specifying a sampling method for selecting items or

events from the frame – Determining the sample size – Implementing the sampling plan – Sampling and data collecting – Reviewing the sampling process

Sampling

• Sampling methods can be split into two distinct groups:

1. Probability samples2. Non-probability samples

Sampling

Probability Samples • Probability samples offer each respondent an

equal probability or chance at being included in the sample.

• They are considered to be:• Objective • Empirical• Scientific• Quantitative• Representative

Types of probability sampling• Simple Random

Sampling– Selected by using chance

or random numbers– Each individual subject

(human or otherwise) has an equal chance of being selected

– Examples: • Drawing names from a hat• Random Numbers

Types of probability sampling• Systematic Sampling– Select a random starting point and then select every kth

subject in the population– Simple to use so it is used often

Types of probability samplingStratified Sampling

Divide the population into at least two different groups with common characteristic(s), then draw SOME subjects from each group (group is called strata or stratum)

Results in a more representative sample

Types of probability samplingCluster Sampling

Divide the population into groups (called clusters), randomly select some of the groups, and then collect data from ALL members of the selected groups

Used extensively by government and private research organizations

Examples:Exit Polls

Sampling

Non Probability Samples• A non probability sample relies on the

researcher selecting the respondents. • They are considered to be:• Interpretivist • Subjective • Not scientific • Qualitative • Unrepresentative

Non-probability Sampling

Convenience Sampling• This involves selecting the nearest and most

convenient people to participate in the research.

• This method of selection is not representative and is considered a very unsatisfactory way to conduct research.

Non-probability SamplingPurposive Sampling• Purposive sampling is selecting a sample “on

the basis of your own knowledge of the population, its elements, and the nature of your research aims”

• It is important to note that purposive sampling precludes that the researcher understand the characteristics clearly and thoroughly enough to choose the sample and relate those findings only to that specific group and not to the population as a whole.

Non-probability SamplingSnowball Sampling• This type of sampling is used when the research is

focused on participants with very specific characteristics such as being members of a gang.

• Having identified and contacted one gang member the researcher asks to be put in touch with any friends or associates who are also gang members.

• This type of sampling is not representative however is useful, especially where the groups in the research are not socially organised i.e. they do not have clubs or membership lists.

Non-probability Sampling

Quota Sampling• Having decided on the characteristics of the

sample frame, a sample is selected to meet these characteristics.

• E.g. if the sample frame is car drivers and the car driving population is 55% male and 45% female then the quota would require the same proportions.

• Participants would be selected to fill this quota using the random method

Errors in Sampling

• Non-Observation Errors– Sampling error: naturally occurs– Coverage error: people sampled do not match the

population of interest– Underrepresentation– Non-response: won’t or can’t participate

Errors of Observation

• Interview error- interaction between interviewer and person being surveyed

• Respondent error: respondents have difficult time answering the question

• Measurement error: inaccurate responses when person doesn’t understand question or poorly worded question

• Errors in data collection