SAMPLING

The Sampling Design Process

Population

The target population is the collection of elements or objects that possess the information sought by the researcher and about which inferences are to be made. The target population should be defined in terms of elements, sampling units, extent, and time.

An element is the object about which or from which the information is desired, e.g., the respondent. A sampling unit is an element, or a unit containing the element, that is available for selection at some stage of the sampling process. Extent refers to the geographical boundaries.Time is the time period under consideration.

SampleSamplingProcess of separating the representative part from population is known as sampling. The method of selecting a specified portion, called a sample, from a population, from which information concerning the whole can be inferred.A portion of the population that represents population characteristics is called as sample. They are the subset of the population that should represent the entire population. They have similar characteristics of population

Population Size: Total number of elements in populationElement: Individual member of populationSample: Representative part of the populationsSample Size: Total number of elements selected from population.Subject: Individual member of sample

Categorization of Sampling methodThere are two categories of sampling method.

Probability based:All those sampling methods in which each and every member of the population gets an equal chance to become the part of the sample.

Non probability based:In non-probability based sampling methods each and every member from the population does not get an equal chance of being selected in the sample.

Probability based sampling methodsSampling procedure in which each and every element of population has a fixed probabilistic chance of being selected for the sample.

Simple Random Sampling (Unrestricted)Complex Random Sampling (restricted)Systematic SamplingStratified Random SamplingCluster Sampling Area SamplingDouble Sampling

Simple random Sampling MethodWith simple random sampling, the probability of selection into the sample is known and equal for all members of population. Sample is selected in such a way that every element of the population has a known and equal chance of being chosen for the sample. Also called random sample. The sample is selected from the entire population i.e. without dividing respondents into groups.

This implies that every number is selected independently of every other element. This method is equivalent to a lottery system.Eg: A lucky draw.Simple random sampling is also known as unrestricted sampling.

Systematic:A probability sampling technique in which the sample is chosen by selecting a random starting point and then picking every nth element in succession from the sampling frame.Eg: pick 3, Then 6 ,9,12,15,18

Using Telephone Dictionary for marketing purposes.

Stratified Sampling MethodA probability sampling technique that uses two step process to partition into subpopulation, or strata . samples are selected from each stratum by a random procedure.Probability samples that force sample to be more representative of the population. It is obtained by dividing the population into groups called strata, then simple random samples are taken from each of the strata. It can be done in two ways: Proportionate & Disproportionate.

Stratified random sampling show more homogeneity within group and heterogeneity across group. FinanceMarketing HR Entrepreneurship.

Proportionate: (Based on relationship)Size:Group size matters a lot.The bigger the size of the strata the more you select, the smaller the size of strata the less you select.

Variance:It depends on the differences that exists in a group. More the difference more you select, the less the difference less you select.

Steps Involved in Stratified Sampling1. Divide the population into stratas or groups.2. Identify the population in each strata.3. Select the number of respondents either proportionately or disproportionately. 4. Select final respondents by applying simple random sampling method

Total PopulationMaleFemale60 students10%40 students10%100 students: 10%64

10 Selecting Numbers of Respondents by ProportionateProportionate ( Size )Larger the size of the group the more we select, the smaller the size of strata the less we select.Strata-1Strata-2

Selecting Numbers of Respondents by ProportionateProportionate ( Variance )More the difference in a group more we select the less the differences in a group the less we select. Total PopulationMaleFemale60 students40 students100 students36dddHere the differences in strata-2 are more than strata-1 and the relationship is 1:2 so for every one respondent from strata-1 well select two respondents from strata-2 untill the desired sample size is achievedStrata-1Strata-2

Disproportionate It is the sampling done without any relationship. Here importance formula is used because the strata size doesnt reflect the relative proportions of the population. It depends on the own judgment of the researcher about the importance of each of the strata for the research. You choose the desired sample size according to your judgment about the importance of the strata in the research.

Total PopulationMaleFemale60 students40 students100 studentsIn this type the Respondent are selected on the Judgment of the Researcher. Researcher decide which group is more important 55Here the researcher thinks that both the strataare equally important for the research. Strata-1Strata-2

Cluster Sampling MethodPopulation is divided into internally heterogeneous subgroups. Some are randomly selected for further study. Advantages:Lowest cost per sample especially with geographical clusters.Easy to do without a population list.

Disadvantages:Often lower statistical efficiency ( more error) due to subgroups being homogenous rather than being heterogeneous.

cluster samples offer more heterogeneity within group and more homogeneity among groups.AfghansNagarkharKabulLaghmanQandhar.

Double SamplingSelecting a sample for the second time for the same study.Already some information is collected, further information is needed for more explanation.

Area SamplingThe Area sampling constitutes on the basis of geographical clusters.

Area Sampling

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Non probability based Sampling methodsIn non-probability based sampling methods each and every member from the population does not get the equal chance of being selected in the sample.It rely on the personal judgment or convenience of the researcher.Less generalize Quick Response

Non-Probability SamplingConvenience SamplingSnow BallPurposive Samplingjudgment SamplingQuota Sampling

Convenience

Convenience samples are sample drawn at the convenience of the researcher. According to most convenient location, time, etc respondents are selected. Convenience sampling may misrepresent the population. A sampling procedure that leaves the selection of respondents totally to the field researcher, with no quotas or qualifications imposed. It consists of those units of the population that are easily accessible.

Snow ballSnowball sampling is commonly used when it is difficult to identify members of the desired population. Make contact with one or two respondents in the population. Ask these new respondents to identify further new respondents and so on. And this process of obtaining data by initial respondent ,and then from referral to referral is called as snow ball.

E.g: Giving the questionnaire to the students who know other students of their batch and then asking them to identify other student whom they know.

JudgmentJudgement sampling is a form of non-probability sampling in which the population elements are selected based on the judgment of the researcher.In judgment sampling researcher uses his/ her own educated guess or judgment to identify who will be in the sample.Only limited people have such information. For Example: Glass Ceiling

Quota The quota sample establishes a specific quota or percentage for various types of individuals to be interviewed. The size of the quota are determined by the researchers belief for relative size of each class of respondent in the population. Often, quota sampling is used as means of ensuring convenience sample sizeQuota Sampling is proportionate stratified sample with convenience based selection.

Quota sampling may be viewed as two-stage restricted judgmental sampling. The first stage consists of developing control categories, or quotas, of population elements. (Strata)In the second stage, sample elements are selected based on convenience or judgment having specific proportion (Proportionate)

PopulationSamplecompositioncompositionControlCharacteristicPercentagePercentageSex Male48048 Female52052________1000100

Strength and weakness of sampling techniquesConvenienceSamplingJudgmentalSamplingQuota samplingSnow Ballsampling

strengthweaknessLeast expensive, least time consuming, most convenient Selection biasness, sample is not representative of (P)Low cost, convenient , less time consumingDoesnt allow generalization, subjective instead of objectiveSample can be controlled from certain characteristics.Selection bias, no assurance of representative.Can estimate rare characteristicsTime consuming

Strength and weakness of sampling techniquesSimple Random

Systematicsampling

Stratified sampling

Cluster sampling

Strength Weakness Easily understood,results are projectableDifficult to construct sampling frame, expensive, lower precision, no assurance of representativeCan increase representative ness, easier to implement, than Srs, Sampling frame not necessary.Can decrease representativeIncludes all important subpopulation, precision.Difficult to select relevant stratification variable, expensive,not feasible to verify many variables.Cost effective , easy implementLow statistical efficiency

Sample vs. Census

Conditions Favoring the Use of

Type of Study

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

High

6. Cost of nonsampling errors

High

Low

7. Nature of measurement

Destructive

Nondestructive

8. Attention to individual cases

Yes

No

Factors to determine sample size1. Cost2. Time3. Importance of decision4. Reliability requirements5. Population size6. Nature of the problem7. Diversity of population

Sample Sizes Used in Research Studies

Type of Study

Minimum Size

Typical Range

Problem identification research (e.g. market potential)

500

1,000-2,500

Problem-solving research (e.g. pricing)

200

300-500

Product tests

200

300-500

Test marketing studies

200

300-500

TV, radio, or print advertising (per commercial or ad tested)

150

200-300

Test-market audits

10 stores

10-20 stores

Focus groups

2 groups

4-12 groups

THE

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