CH10 Sampling

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Chapter 10

Sampling

2009 John Wiley & Sons Ltd.www.wileyeurope.com/college/seka

Reference Books for Sampling:Research Methods for business students chapter-6

Research Methods for Graduate business and Social Science students Chapter - 5


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Sampling

Sampling: theprocess of selecting a sufficientnumber of elements from the population, sothat results from analyzing the sample are

generalizable to the population.

2 2009 John Wiley & Sons Ltd.www.wileyeurope.com/college/seka


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Relevant Terms - 1

Population refers to the entire group ofpeople, events, or things of interest thatthe researcher wishes to investigate.

An elementis a single member of thepopulation.

A sample is a subset of the population.It comprises some members selectedfrom it.



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Relevant Terms - 2

Sampling unit(individuals, HH, cityblocks etc.):the element or set ofelements that is available for selection

in some stage of the sampling process.

A subjectis a single member of the

sample, just as an element is a singlemember of the population.



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Relevant Terms - 3

The characteristics of thepopulation such as (the populationmean), (the population standard

deviation), and 2 (the populationvariance) are referred to as itsparameters.The central tendencies,the dispersions, and other statistics inthe sample of interest to the researchare treated as approximations of thecentral tendencies, dispersions, and

other parameters of the population Sam le statistics.5 2009 John Wiley & Sons Ltd.www.wileyeurope.com/college/seka


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Statistics versusParameters



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Advantages of Sampling

Less costs

Less errors due to less fatigue

Less time Destruction of elements avoided



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The Sampling Process

Major steps in sampling: Define the population. (e.g saving habits of blue

collars employees in mining industry- population ?,reading habits of retired women in Punjab)

Determine the sample frame (e.g list ofpopulation under study- telephone users list may notbe latest)

Determine the sampling design ( probability or

Non probability sampling method- PS= known or nonzero chances of being selected as sample ofelements-generalizability NPS= when chances ofbeing selected are not known, time constraint,generalizability is not priority)

Determine the appropriate sample size(Research objectives, confidence interval, confidence

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Sampling Techniques

1- Probability

2- nonprobability sampling

Probability sampling: elements in thepopulation have a known and non-zerochance of being chosen



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Sampling Techniques

Probability Sampling

Simple Random Sampling

Systematic Sampling

Stratified Random Sampling

Cluster Sampling

Nonprobability Sampling

Convenience Sampling

Purposive Sampling Judgment Sampling

Quota Sampling

Snow Ball sampling



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Simple Random Sampling

Procedure Each element has a known and equal chance of being

selected

Characteristics Highly generalizable

Easily understood

Reliable population frame necessary



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Systematic Sampling

Procedure Each nth element, starting with random choice of an

element between 1 and n

Characteristics Idem simple random sampling

Easier than simple random sampling

Systematic biases when elements are not randomly

listed



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Stratified Sampling

Procedure Divide of population in strata

Include all strata

Random selection of elements from strata

Proportionate Disproportionate

Characteristics Interstrata heterogeneity

Intrastratum homogeneity

Includes all relevant subpopulations



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Proportionate Disproportionate StratifiedSampling

Number of subjects in total sample is allocatedamong the strata proportional ordisproportional to the relative number ofelements in each stratum in the population

Disproportionate case: strata exhibiting more variability are sampled more

than proportional to their relative size

requires more knowledge of the population, not justrelative sizes of strata



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Proportionate and disproportionateStratified Random Sampling

Top Management Number ofElements

ProportionateSampling (20%of theElements)

Disproportionate Sampling

Middle LevelManagement

10 2 7

Lower levelManagement

30 6 15

Supervisors 50 10 20

Clerks 100 20 30Secretaries 500 100 60

TotalS 20 4 10

710 142 142


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Cluster Sampling

Target population is divided into clusters then randomsampling ( either simple or systematic) is done withinthe clusters.

Cluster samples offer more homogeneity among groups

and more heterogeneity within a group. It is least generalizable in probability sampling because

clusters may or may not have heterogeneity. But this ischeapest sampling method.

e.g. area sampling

Multistage cluster sampling

e.g. urban, semi urban and rural area sampling- location isselected then banks are selected. Random sampling sdone to choose each unit at every stage in this type odsampling.


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Non Probability Sampling

Convenience sampling=collection ofinformation from members of the populationwho can provide it.

(e.g. Pepsi preference contest at shopping mall- shoppers areasked about ------------)-

This method is important during the exploratory stage of theproject and perhaps best way of getting basic information

Purposive sampling= to get information from

specific target groups. ( from specific group-who canonly provide relevant information-types as follows) Judgment sampling( e.g. women at top management

positions- fewer respondents available, PS isuseless )

Quota sampling= it ensures that certain group areadequately represented I the study thorough the


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Non Probability Sampling

Quota sampling is akin to proportionate stratifiedsampling

white collar and blue collar workers differenceassessment-60% blue collar and 40 % white collar

people to be included in the sample but data iscollected through convenient sampling.

Snowball sampling


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Overview



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Overview



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Overview



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Choice Points in Sampling Design



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Tradeoff between precision andconfidence

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We can increase both confidence and precision byincreasing the sample size



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Sample size: guidelines

In general: 30 < n < 500

Categories: 30 per subcategory

Multivariate: 10 x number of vars

Experiments: 15 to 20 per condition



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Sample Size for a GivenPopulation Size



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Sample Size for a Given


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