project - sampling techniques

8/3/2019 Project - Sampling Techniques

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SamplingTechniquesPresented By:

SMBA 16 - Pratik Shah - 12


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What is SAMPLING?

Sampling is the process of selecting units (e.g.,

people, organizations) from a population of

interest so that by studying the sample we mayfairly generalize our results back to the population

from which they were chosen .


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Sampling Process

Units of Analysis (people) List or Procedure

Target Population

Population of Interest Sampling Frame

List or Rule

Defining the Population

Actual Population to WhichGeneralizations Are Made

Defined/Listed by Sampling Frame Method of

selection

List of Target Sample

Target Sample

Response

RateSample

The people

actually studied

Generalization


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Method of SAMPLING

Probability Non-Probability

SimpleRandom Sampling

Systematic Sampling

StratifiedR

andom Sampling

Cluster Sampling

Multistage and Multi Phase Sampling

Convenience Sampling

Purposive Sampling

Quota Sampling


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Probability Sampling


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Simple Random Sampling

Each element in the population has an equal

probability of selection AND each combination of

elements has an equal probability of selectione.g.

Names drawn out of a hat

Random numbers to select elements from an

ordered list


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Systematic Sampling

Each element has an equal probability of selection,but combinations of elements have differentprobabilities.

Population size N, desired sample size n, samplinginterval k=N/n.

Randomly select a number j between 1 and k, sampleelement j and then every kth element thereafter, j+k,

j+2k, etc.

e.g.

N=64, n=8, k=64/8=8.Random j=3.


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Stratified Random Sampling

A method of sampling that involves the division of apopulation into smaller groups known as strata. Instratified random sampling, the strata are formedbased on members' shared attributes orcharacteristics. A random sample from each stratumis taken in a number proportional to the stratum's sizewhen compared to the population. These subsets ofthe strata are then pooled to form a random sample.

e.g.

A state could be separated into counties, a schoolcould be separated into grades. These would be the'strata'.


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Cluster Sampling

With cluster sampling, the researcher divides the

population into separate groups, called clusters.

Then, a simple random sample of clusters isselected from the population. The researcher

conducts his analysis on data from the sampled

clusters.


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Multistage and Multi Phase Sampling

Large national probability samples involve severalstages of stratified cluster sampling

The whole country is divided into geographicclusters, metropolitan and rural

Some large metropolitan areas are selected withcertainty (certainty is a non-zero probability!)

Other areas are formed into strata of areas (e.g.

middle-sized cities, rural counties); clusters areselected randomly from these strata


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Non Probability Sampling


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Convenience Sampling

It is a technique where subjects are selectedbecause of their convenient accessibility andproximity to the researcher.

e.g.

Using subjects that are selected from a clinic, aclass or an institution that is easily accessible tothe researcher. A more concrete example ischoosing five people from a class or choosing thefirst five names from the list of patients.


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Purposive Sampling

It is use to access a particular subset of people.

When taking the sample, reject people who do not fit a

particular profile.

e.g.

A researcher wants to get opinions from non-working

mothers. They go around an area knocking on doors

during the day when children are likely to be at school.They ask to speak to the 'woman of the house. Their

first questions are then about whether there are

children and whether the woman has a day job.


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Quota Sampling

The basic objective of quota sampling is to controlbiases arising out of non-probability method by

stratification and the setting of quotas for eachstratum.

e.g.

A sample of 40 students can be selected from agroup of 200 students comprising of 120 boys and 80

girls. To make the sample representative, the group of40 should include 24 boys and 16 girls (i.e. 120: 80 =3: 2).


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project - sampling techniques

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