RSCH 410 SAMPLING METHODS

DR. MONA HASSAN

Sampling technique

It is a procedure where we select a

group of subjects (a sample) for study

from a larger group (a population)

Why do sampling A large proportion of individuals or items

or units have to be studied, we take a sample

Easier and economical to study sample than the whole population

Items in the sample are representative of the whole population to be studied

Target population

The population to which the

investigator wishes to generalise

The population of sampling units

from which we draw our sample.

For practical reasons, the study

population is often more limited than

the target population

Study population (Survey population)

Sample

A subset of the population, selected

so as to be representative of the

larger population

Sampling

Sampling frame:

The set of sampling units from which

a sample is to be selected.

E.g. a list of names, or places etc.

Sampling Sampling unit:

The unit of selection in the sampling process.

E.g. a person, a household or a district.

It is not necessarily the unit of observations or

study

Types A probability sampling : in which every

unit in the population has the same chance

or probability of selection.

Non probability sampling : is any sampling

method where some elements of the

population have no chance of selection

Probability Sampling

Simple random sampling Each element of the frame thus has an equal

probability of selection

Minimizes bias and simplifies analysis of result

SRS can be vulnerable to sampling errors may

result in a sample that doesn't reflect the

makeup of the population(male : female)

Advantages:

1. Easy to estimate the accuracy of results

2. Easy &simply

Disadvantages:

1. A sample that doesn't reflect the makeup of

the population.

2. It does not provide subsamples of the

population.

Systematic sampling relies on arranging the target population on

ordered list and then selecting elements at

regular intervals.

Advantages:

1. It is easy to implement.

2. the stratification can make it efficient.

Disadvantages:

1. The sample likely to be unrepresentative,

making the study less accurate

2. Difficult to quantify that accuracy.

Stratified sampling The population frame can be organized by categories

into separate strata. Then individual elements can be

randomly selected.

Potential benefits:

1. Enable researchers to draw inferences about specific

subgroups.

2. Can lead to more efficient statistical estimates.

3. Enabling researchers to use the data collection

approach best suited for each subgroup.

Potential drawbacks:

1. Increase the cost and complexity of sample

selection.

2. Can potentially require a larger sample than

would other methods.

A stratified sampling approach is most effective

when:

1. Variability within strata are minimal.

2. Variability between strata are maximum.

Cluster sampling To select respondents in groups ('clusters').

Sampling is clustered by geography, or by time periods.

It requires a larger sample than SRS to achieve the same level of accuracy.

It is commonly implemented as multistage sampling

Advantages:1. Can reduce travel and administrative costs.2. Does not need a sampling frame.

Non Probability Sampling

Convenience sampling

This sample would not be representative enough.

This type of sampling is most useful for pilot testing.

Quota sampling One of non-probability sampling.

The population is first segmented into

mutually exclusive sub-groups.

Then selection of the sample ( which is non-

random) based on a specified proportion.

Disadvantage: These samples may be

biased.

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