Types sampling methods

8/18/2019 Types sampling methods

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SAMPLING AND

ITS TYPES


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SAMPLING

Target Population or Universe

The population to which the investigator wants togeneralize his results

Sampling Unit:

smallest unit from which sample can be selected

Sampling frame

The sampling frame is the list from which the potentialrespondents are drawn Telephone director List of five star !otel List of student

Sampling sceme

Method of selecting sampling units from sampling frame

Sample" all selected respondent are sample


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SAMPL#

TA$G#T P%P&LATI%N

SAMPL# &NIT

SAMPL#

• A population can be defined as including all people or itemswith the characteristic one wishes to understand'

• (ecause there is ver rarel enough time or mone to gather

information from everone or everthing in a population) the

goal becomes finding a representative sample *or subset+ of

that population'


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SAMPLING ($#A,-%.N

All university in India

All university Haryana

List of Haryana university

Three university in haryana


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SAMPLING……

To whom do ou want to generalize our results0All 1ive Star !otel

All Travel Agenc

All !otel 2ustomer

.omen aged 34564 ears%ther

Sample size " Minimum size is 78 no'


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SAMPLING$$%

7 factors that influence sample representative5nessSampling procedureSample size

Participation *response+

.hen might ou sample the entire population0.hen our population is ver small

.hen ou have e9tensive resources.hen ou don/t e9pect a ver high response


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The sample must be"3' representative of the population:

;' appropriately sized *the larger the better+:

7' unbiased :

6' random *selections occur b chance+:

!at is Goo& Sample#

Merits of SamplingSize of population1und re


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T'E (ESP(ESENATI)N *ASIS P$%(A(ILIT= SAMPLING N%N P$%(A(ILIT= SAMPLING

ELEMENT SELE+TI)N TE+'NI,E

$#ST$I2T#- SAMPLING &N $#ST$I2T#- SAMPLING

TYPES )- SAMPLE *ASED )N T!) -A+T)(S:


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•Probability sample – a method of sampling thatuses of random selection so that all units/ cases inthe population have an equal probability of being

chosen.• Non-probability sample – does not involverandom selection and methods are not based onthe rationale of probability theory.

Types of Sampling

Sampling

Techniques

Probability Non-

Probability


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Probabilit *$andom+ Samples Simple random sample

Sstematic random sample

Stratified random sample

2luster sample

Probabilit

Sampling

Simple

$andom

Sampling

Sstematic

Sampling

Stratified

$andom

Sampling

Proportionate-is Proportionate

2luster

Sampling

%ne5

Stage

Two

Stage

Multi5

Stage


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Non5Probabilit Samples

2onvenience samples *ease of access+

sample is selected from elements of a population thatare easil accessible

Purposive sample *>udgmental Sampling+

=ou chose who ou thin? should be in the stud@uota Sampling

Snowball Sampling *friend of friend'etc'+

Non5

Probabilit

2onvenience

Sampling

@uota

Sampling

>udgment

Sampling

Snowball

Sampling


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Difference .et/een Pro.a.ilit"

sampling an& Non Pro.a.ilit"


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SIMPLE (AND)M SAMPLING• Applicable when population is small) homogeneous B

readil available• All subsets of the frame are given an e


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Simple random sampling

Ever" su.set of a specifie& si0e n from te population

as an e1ual cance of .eing selecte&


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Suita.ilit"

This method is suitable for small homogeneous $andoml selecting units from a sampling frame'

C$andom/ means mathematicall each unit from the

sampling frame has an e


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(EPLA+EMENT )- SELE+TED UNITS

Sampling schemes ma be without replacement or with

replacement

1or e9ample) if we catch fish) measure them) and

immediatel return them to the water before continuingwith the sample) this is a with replacement design)

because we might end up catching and measuring the

same fish more than once' !owever) if we do not return

the fish to the water *e'g' if we eat the fish+) this becomesa without replacement design'


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• Similar to simple random sample' No table of random

numbers D select directl from sampling frame' $atio

between sample size and population size

S"stematic Sampling

-efine population

-evelopsampling

frame

-ecide thesample size

.or? outwhat fractionof the framethe sample

sizerepresents

Selectaccording tofraction *388sample from

3)888 frame then38E so ever

38th unit+

1irst unitselect brandomnumbers

then evernth unitselected

*e'g' ever38th+


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AD2ANTAGES: Sample eas to select

Suitable sampling frame can be identified easil

Sample evenl spread over entire reference population 2ost effective

DISAD2ANTAGES:

Sample ma be biased if hidden periodicit in populationcoincides with that of selection'

#ach element does not get e


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Systematic sampling

#ver member * for e9ample" ever ;8th person+ is

selected from a list of all population members'


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Stratifie& (an&om Sample

The population is divided into two or more groupscalled strata) according to some criterion) such as

geographic location) grade level) age) or income) and

subsamples are randoml selected from each strata'


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Stratied RandomSample

e!nepopulation

evelopsampling

frameaccording to

characteristicsrequired

etermine theproportion of

eachpopulationvariable of

interest

Systematicsampling

methods canthen be follo$edto select sample

unit

Stratified random sampling can be classified in to

a% Proportionate stratifie& sampling

It involves drawing a sample from each stratum in

proportion to the letter/s share in total population

b' Disproportionate stratifie& sampling proportionate representation is not given to strata

it necesser involves giving over representation to

some strata and under representation to other'


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ST$ATI1I#- SAMPLINGA&vantage :

Enancement of representativeness to eac sample 'iger statistical efficienc" Eas" to carr" out

Disa&vantage:

+lassification error Time consuming an& e3pensive Prior 4no/le&ge of composition an& of

&istri.ution of population


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+LUSTE( SAMPLING 2luster sampling is an e9ample of Ftwo5stage samplingF '

1irst stage a sample of areas is chosen: Second stage a sample of respondents within those areas is

selected'

Population divided into clusters of homogeneous units) usuall

based on geographical contiguit' Sampling units are groups rather than individuals'

A sample of such clusters is then selected'

All units from the selected clusters are studied' The population is divided into subgroups *clusters+ li?e

families' A simple random sample is ta?en of the subgroups

and then all members of the cluster selected are surveed

%luster sampling


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%luster sampling

Section 4

Section 5

Section 3

Section 2Section 1


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2L&ST#$ SAMPLING'

Advantages "

2uts down on the cost of preparing a samplingframe' This can reduce travel and otheradministrative costs'

-isadvantages" sampling error is higher for a simple

random sample of same size' %ften used to evaluate

vaccination coverage in #PI


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• +luster sampling" selecting a sample based on specific) naturall occurring

groups *clusters+ within a population'

5 #9ample" randoml selecting ;8 hospitals from a list of all

hospitals in #ngland'

Multi5stage sampling" cluster sampling repeated at a number of levels' 5

#9ample" randoml selecting hospitals b count and then a sample of patientsfrom each selected hospital'

2omple9 form of cluster sampling in which two or more levels of units areembedded one in the other'

1irst stage) random number of districts chosen in all states'

1ollowed b random number of talu?as) villages' Then third stage units will be houses'

All ultimate units *houses) for instance+ selected at last step are surveed'

+luster6 multi5stage ran&om sample


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-ifference (etween Strata and 2lusters

Although strata and clusters are both non5overlappingsubsets of the population) the differ in several was'

All strata are represented in the sample: but onl asubset of clusters are in the sample'

.ith stratified sampling) the best surve results occurwhen elements within strata are internallhomogeneous' !owever) with cluster sampling) the

best results occur when elements within clusters areinternall heterogeneous


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Non Pro.a.ilit"

+)N2ENIEN+E SAMPLING

Sometimes ?nown as gra. or opportunit" sampling or acci&ental or apa0ar&

sampling% Selection of whichever individuals are easiest to reach

It is done at the convenienceH of the researcher 1or e9ample) if the interviewer was to conduct a surve at a

shopping center earl in the morning on a given da) the peoplethat heshe could interview would be limited to those given thereat that given time) which would not represent the views of othermembers of societ in such an area) if the surve was to beconducted at different times of da and several times per wee?'

This tpe of sampling is most useful for pilot testing' In social science research) snowball sampling is a similar

techni


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Adantage! A sample selected for ease of

access& immediately 'no$n population group andgood response rate.

"isadantage! cannot generalise !ndings (donot 'no$ $hat population group the sample is

representative of) so cannot move beyonddescribing the sample.

•*roblems of reliability

•o respondents represent thetarget population

•"esults are not generali#able

+onvenience Sampling

Sunil +umarUse results that are eas to et


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7u&gmental sampling or Purposive sampling 5 The researcher chooses the sample based on who

the thin? would be appropriate for the stud' This isused primaril when there is a limited number of

people that have e9pertise in the area being

researched

Selected based on an e9perienced individual/s belief Advantages

(ased on the e9perienced person/s Judgment

-isadvantages 2annot measure the respresentativeness of the

sample


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,U)TA SAMPLING

The population is first segmented into mutuall e9clusive sub5groups) Just as in stratified sampling'

Then Judgment used to select subJects or units from each segment based on a specified proportion'

1or e9ample) an interviewer ma be told to sample ;88 femalesand 788 males between the age of 64 and K8'

It is this second step which ma?es the techni


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,uota sampling

(ased on prespecified


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Sno/.all Sampling &seful when a population is hidden or difficult to gain access to' The

contact with an initial group is used to ma?e contact with others' $espondents identif additional people to included in the stud

The defined target mar?et is small and uni


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*otential Sources of ,rror in "esearch esigns

S#rrogate $nformation%rror

&eas#rement %rror

Pop#lation "enition

%rrorSampling 'rame %rror

Respondent Selection%rror

(#estioning %rror

Recording %rror

)*eating %rror

$nability %rror

+n,illingness%rror

Total %rror

Non-sampling%rror

RandomSampling

%rror

Non-response%rror

Response%rror

$nterie,er

%rror

Respondent

%rror

Researc*er

%rror

, i H it lit


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,rrors in Hospitality"esearch

The total error is the variation bet$een the true mean value in

the population of the variable of interest and the observed meanvalue obtained in the mar'eting research pro-ect.

Random sampling error is the variation bet$een the true meanvalue for the population and the true mean value for the originalsample.

Non-sampling errors can be attributed to sources other than

sampling& and they may be random or nonrandom includingerrors in problem de!nition& approach& scales& questionnairedesign& intervie$ing methods& and data preparation and analysis.on0sampling errors consist of non0response errors and responseerrors.

Non-response error arises $hen some of the respondents

included in the sample do not respond. Response error arises $hen respondents give inaccurate

ans$ers or their ans$ers are misrecorded or misanaly#ed

S li


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• The larger the sample si#e the more li'ely errorin the sample $ill decrease.

•1ut& beyond a certain point increasing samplesi#e does not provide large reductions in samplingerror.

•Accuracy is a re2ection of the sampling error and

con!dence level of the data.

Sampling %rrorand )ondence


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,rrors in Sampling

on03bservation ,rrors Sampling error naturally occurs

%overage error people sampled do not

match the population of interest 4nderrepresentation

on0response $on5t or can5t participate


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,rrors of 3bservation

Intervie$ error0 interaction bet$eenintervie$er and person being surveyed

"espondent error respondents have

di6cult time ans$ering the question 7easurement error inaccurate

responses $hen person doesn5tunderstand question or poorly $orded

question ,rrors in data collection

Sunil +umar


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Types sampling methods

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