08BRM Sampling Design and Procedures

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Sampling: Design and Procedures

Business Research Methods


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Sample or Census Population: The aggregate of all elements,

sharing some common set of characteristics, thatcompromises the universe for the purpose ofresearch problem.

Census: A complete enumeration of the elements

of a population or study objects.

Sample: A subgroup of the elements of thepopulation selected for participation in the study.


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Sample Vs CensusSample versus Census

CONDITIONS FAVORING THEUSE OF

SAMPLE CENSUS

1. Budget Small Large

2. Time available Short Long

3. Population size Large Small

4. Variance in the characteristic Small Large

5. Cost of sampling errors Low High6. Cost of nonsampling errors High Low

7. Nature of measurement Destructive Nondestructive

8. Attention to individual cases Yes No


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The Sampling Design Process Target Population: The collection of elements or

objects that possess the information sought bythe researcher and about which inferences are tobe made.

Element: Objects that possess the information

sought by the researcher and about whichinferences are to be made.

Sampling Unit: The basic unit containing the

elements of the population to be sampled.


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The Sampling Design Process Define the target population

Determine the sampling scope

Select a sample technique(s)

Determine the sampling size Execute the sampling process


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Target Population

The target population for a department store projectmay be defined as follows:

Elementsmale or female head of the householdresponsible for most of the shopping atdepartment stores.

Sampling unitshouseholds

ScopeMetro Cities

Time

2011


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Select a Sampling Technique Sampling with replacement: A sampling

technique in which an element can be included inthe sample more than once.

Sampling without replacement: A samplingtechnique in which an element cannot be

included in the sample more than once.


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A Classification of SamplingTechniques

1. Nonprobability1. Convenience Sampling

2. Judgmental Sampling

3. Quota Sampling

4. Snowball Sampling

2. Probability1. Simple Random Sampling

2. Systematic Sampling

3. Stratified Sampling1. Proportionate

2. Disproportionate

4. Cluster Sampling

5. Other Sampling Techniques


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Nonprobability Sampling

Sampling techniques that do not use chanceselection procedures. Rather, they rely on thepersonal judgment of the researcher.


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Probability Sampling

A sampling procedure in which each element of thepopulation has a fixed probabilistic chance ofbeing selected for the sample.


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Nonprobability Sampling Techniques

Convenience Sampling: Convenience samplingattempts to obtain a sample of convenientelements. The selection of sampling units is leftprimarily to the interviewer. Often, respondents

are selected because they happen to be in theright place at the right time.


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Judgmental Sampling: Judgmental sampling isa form of convenience sampling in which thepopulation elements are selected based on thejudgment of the researcher. The researcher,

exercising judgment or expertise, chooses theelements to be included in the sample, becausehe or she believes that they are representative ofthe population of interest or are otherwise

appropriate.


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Quota Sampling: Quota sampling may beviewed as two-stage restricted judgmentalsampling, where the first stage consists ofdeveloping control categories, or quotas, of

population elements.


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Snowball Sampling: In snowball sampling, aninitial group of respondents is selected, usually atrandom. After being interviewed, theserespondents are asked to identify others who

belong to the target population of interest.Subsequent respondents are selected based onreferrals. This process may be carried out inwaves by obtaining referrals from referrals, thus

leading to a snowballing effect.


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Probability Sampling Techniques Simple Random Sampling: In simple random

sampling (SRS), each element in the populationhas a known and equal probability of selection.Furthermore, each possible sample of a given

size (n) has a known and equal probability ofbeing the sample actually selected.


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Sampling Frame

A B C D E

1 6 11 16 21

2 7 12 17 22

3 8 13 18 23

4 9 14 19 24

5 10 15 20 25


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Probability Sampling Techniques Systematic Sampling: In systematic sampling,

the sample is chosen by selecting a randomstarting point and then picking every ith elementin succession from the sampling frame. The

sampling interval, i, is determined by dividing thepopulation size N by the sample size n androunding to the nearest integer.


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Probability Sampling Techniques Stratified Sampling: Stratified sampling is a two-

step process in which the population is partitionedinto subpopulations, or strata. The strata shouldbe mutually exclusive and collectively exhaustive.

Every population element should be assigned toone and only one stratum and no populationelements should be omitted. Next, elements areselected from each stratum by a random

procedure, usually SRS.


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Probability Sampling Techniques Cluster Sampling: In cluster sampling, the target

population is first divided into mutually exclusiveand collectively exhaustive subpopulations, orclusters. The a random sample of clusters is

selected, based on a probability samplingtechnique such as SRS.


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Difference Between Stratified andCluster Sampling

Factor Stratified Sampling Cluster Sampling (onestage)

Objective Increase precision Decrease cost

Subpopulations All strata are included A sample of clusters is

chosen

Withinsubpopulations

Each stratum shouldbe homogeneous

Each cluster should beheterogeneous

Acrosssubpopulations Strata should beheterogeneous Clusters should behomogeneous

Sampling frame Needed for the entirepopulation

Needed only for the selectedclusters

Selection of Elements selected All elements from each


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Choosing Nonprobability VsProbability Sampling

Choosing Nonprobability Vs Probability Sampling

CONDITIONS FAVORING THE USE OF

FACTORS NONPROBABILITYSAMPLING

PROBABILITYSAMPLING

Nature of research Exploratory Conclusive

Relative magnitude ofsampling andnonsampling errors

Nonsampling errorsare larger

Sampling errors arelarger

Variability in thepopulation

Homogeneous (low) Heterogeneous(high)

Statistical considerations Unfavorable Favorable

Operational

considerations

Favorable Unfavorable

08BRM Sampling Design and Procedures

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