A level Sociology

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Theory and Methods Collecting Sociological Data

A Level Sociology

Teaching Notesfor Students

Theory and Methods:

Sampling Techniues

Chris.Livesey: www.sociology.org.uk Page 1


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Sampling Techniues

Simple !andom sample

Systematic sample

Stratified !andom sample

Stratified "uota sample

Sno#$all sample

Multi%stage &Cluster' sample

Multi%phase sample(

The )ey ideas here are:

Target Population

Sample Size

Representative Sample

Sampling Frame

Sampling Types

Sampling rrors

!henever a sociologist starts a piece o" research# they always have in min$ a group o"people they want to stu$y. These people# whoever they may %e# are known as the targetpopulation an$ are# in e""ect# everyone in a particular group you woul$ like to research.

&our target population might# "or e'ample# %e a small group (perhaps 1) or 1* people in all+ whoseem to meet regularly in your local park.

,n the other han$# your target population might %e the -)#))) "oot%all "ans who atten$anchester /nite$0s home games at ,l$ Tra""or$.

" you think a%out these e'amples# it might %e "airly easy to $o some research on the "irstgroup# since the target population is small. !hether this research involves o%serving thegroup "rom a $istance# asking them 2uestions# participating in their %ehaviour orwhatever# the size o" the group makes it relatively easy to manage your research.

!ith the secon$ e'ample# however# things might %e more $i""icult# since its size is goingto make it very har$ "or you to personally o%serve or 2uestion everyone in it. This#there"ore# is where the concept o" sampling comes into its own...

!hen you# as a sociological researcher# take a sample o" a population to stu$y all you

are $oing is looking at a relatively small num%er o" people who %elong to that group.

n the secon$ case# "or e'ample# you might $eci$e to choose 1)) anchester /nite$ "ans toresearch an$# %y stu$ying their %ehaviour# hope to say something a%out the characteristics or%ehaviour o" all o" the "ans in your target population.

!henever you take a sample# there"ore# you are imme$iately choosing a certain num%ero" people "rom a much larger group# which %rings us to the 2uestion o" sample size3 howlarge or how small# "or e'ample# shoul$ your sample %e4

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5lthough this may# at "irst sight# seem to %e an important 2uestion (is a 6)7 sample toolarge or a 1)7 sample too small4+ it8s one that actually has no correct answer.

9ot only is there no correct answer# the 2uestion itsel" can actually %e consi$ere$ largelyirrelevant in the conte't o" social research. ," much greater signi"icance than the2uestion o" how many or in$ee$ how "ew people you have in your sample is that o"representativeness.

This is an important i$ea which# in %asic terms# means:;5re the people you0ve chosen "or your sample representative o" your target population4


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!hat this means is that# when testing an i$ea you $eli%erately choose a sample that willprovi$e the %est possi%le opportunity to show that the i$ea is true.

" your research shows the i$ea to %e "alse "or this =%est opportunity= group then it "ollowsthat there is a high pro%a%ility that it will %e "alse "or any other relevant groups.

Finally# there may %e instances when it is simply not possi%le to construct arepresentative sample "or a group you want to stu$y.

5n e'ample here might %e research into =secretive= organisations such as some religious groupswho re"use to $isclose $etails o" their mem%ership to =outsi$ers=. " you want to research suchgroups it will not %e possi%le to know with any $egree o" certainty that the group mem%ers youactually stu$y are representative o" everyone who is a mem%er o" the organisation.

The name we give to this type o" sample is =snow%all= or =opportunity= sampling an$ thisis $iscusse$ in more $etail in the section on =Types o" Sampling=.

*+amples of Non%!epresentative Sampling

1. ;The 5""luent !orker n The Class Structure


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!allis was intereste$ in stu$ying a religious group calle$ The Church o" Scientology(;Scientologists


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>owever# ?ust %ecause a list G sampling "rame e'ists# it $oesn8t mean a researcher willautomatically have access to it.

For e'ample# it is 2uite possi%le that access to a sampling "rame may %e $enie$ on the%asis o":

Legal reasons(

5 school# "or e'ample# is unlikely to give an outsi$e researcher access to theirregisters.

Confidentiality(

5 %usiness organisation is unlikely to give an outsi$e researcher access to theirpayroll recor$s.

Secrecy.

Some religious groups# political parties an$ so "orth $o not want outsi$eresearchers to stu$y their activities.

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Complete the follo#ing uestions: (I Jelete those wor$s that $o not apply+

1. 5n appropriate sampling "rame "or research on the voting intentions o" people in Jorset woul$%e

t woul$ %e Ieasy G $i""icult G impossi%le to get access to this sampling "rame %ecause:

*. 5n appropriate sampling "rame "or research into "amilies with new%orn %a%ies in my townwoul$ %e


@. 5n appropriate sampling "rame "or research into registere$ $ruga$$icts in 9ewcastle woul$ %e


. 5n appropriate sampling "rame "or research into stu$ents in my school G college woul$ %e


H. 5n appropriate sampling "rame "or research into em%ers o" Parliament in Dritain woul$ %e


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.n your o#n #ords/ outline the difference $et#een representative and non%representative forms of sampling( 0lease include an e+ample of each in yourans#er(

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1ive one reason #hy a researcher might use a representative sample(

1ive one reason #hy a researcher might use a non%representative sample(



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Types of Sampling2( Simple !andom Sampling

This is one o" the most %asic (simple+ "orms o" sampling# %ase$ on the pro%a%ility that the

ran$om selection o" names "rom a sampling "rame will pro$uce a sample that isrepresentative o" a target population. n this respect# a simple ran$om sample is similar toa lottery:

veryone in the target population is i$enti"ie$ on a sampling "rame.

The sample is selecte$ %y ran$omly choosing names "rom the "rame until the

sample is complete.

For e'ample# a *)7 sample o" a target population o" 1)) people woul$ involve theran$om selection o" *) people to %e in the sample.

5n e'ample o" a simple ran$om sample you coul$ easily construct woul$ %e to take the names o"every stu$ent in your class "rom the register# write all the names on separate pieces o" paper an$put them in a %o'.

" you then $raw out a certain percentage o" names at ran$om you will have constructe$ yoursimple ran$om sample

3( Systematic Sampling

5 variation on the a%ove is to select the names "or your sample systematically rather thanon a simple ran$om %asis. Thus# instea$ o" putting all the names on your sampling "rame

in$ivi$ually into a %o'# it8s less trou%le to select your sample "rom the sampling "rameitsel".

For e'ample# i" you were constructing a *)7 sample o" a target population containing 1))names# a systematic sample woul$ involve choosing every "ourth name "rom yoursampling "rame.

5 simple e'ample o" a systematic sample woul$ %e "or you to use a class register to construct asample o" stu$ents in your class.

&ou coul$ try constructing a H)7 sample o" your class using this sampling techni2ue.

This type o" sampling techni2ue ten$s to %e use$ when the target population is verylarge.

For e'ample# i" you were going to select a 1)7 sample "rom a target population o" 1 millionpeople you woul$ either nee$ a very large %o' an$ a lot o" patience or a computer an$ somemeans o" getting the names in your target population into a program that woul$ select yoursample ran$omly

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Doth o" the a%ove types o" sampling are very similar# %ut the main $i""erence %etweenthem is that while simple ran$om samples are truly ran$om (everyone in the targetpopulation has an e2ual chance o" %eing chosen "or the sample+# systematic samples areonly nearran$om (or pseu$oran$om+.

Systematic samples are nearran$om %ecause i" you have a list o" 1)) people# "ore'ample# an$ you start to select a *)7 sample %eginning with the "irst name on yoursampling "rame# the secon$# thir$ an$ "ourth names actually have no chance o" %einginclu$e$ in your sample...

!hen $eci$ing which o" these two types o" sampling to use# their %asic a$vantages an$$isa$vantages are very similar an$ we can summarise them in the "ollowing terms:

-ses:

1. Doth are relatively 2uick an$ easy ways o" selecting samples (i" the targetpopulation is reasona%ly small+.

*. They are ran$om G near ran$om# which means that everyone in the targetpopulation has an e2ual chance o" appearing in the sample (this is not 2uite true o"systematic sampling# %ut such samples are ;ran$om enough< "or most researchpurposes+.

@. They are %oth reasona%ly ine'pensive to construct. Doth simply re2uire asampling "rame that is accurate "or the target population.

. ,ther than some means o" i$enti"ying people in the target population (a namean$ a$$ress# "or e'ample+# the researcher $oes not re2uire any other knowle$ge

a%out this population (an i$ea that will %ecome more signi"icant when we consi$ersome other "orms o" sampling+

Limitations

1. The "act that these types o" sample always nee$ a sampling "rame means that#in some cases# it may not %e possi%le to use these types o" sampling. For e'ample#a stu$y into ;un$erage $rinking< coul$ not %e %ase$ on a simple ran$om orsystematic sample %ecause no sampling "rame e'ists "or the target population.

*. n many cases a researcher will want to get the views o" $i""erent categories o"people within a target population an$ it is not always certain that these types o"

sampling will pro$uce a sample that is representative o" all sha$es o" opinion.

For e'ample# in a classroom it might %e important to get the views o" %oth theteacher an$ their stu$ents a%out some aspect o" e$ucation. 5 simple ran$om Gsystematic sample may not inclu$e a teacher %ecause this category is likely to %ea very small percentage o" the overall class3 there is a high level o" pro%a%ility thatthe teacher woul$ not %e chosen "or %y any sample that is simply %ase$ onchance



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,ne way o" trying to overcome some o" the potential limitations o" simple ran$om Gsystematic sampling is to use an alternative sampling techni2ue that avoi$s the pro%lemo" possi%le un$errepresentation# while retaining the i$ea o" selection %ase$ on chance.

This type o" sampling is calle$ Strati"ie$ sampling an$ we can look %rie"ly at this i$eane't.

4( Stratified !andom Sampling(

5s a simple way o" illustrating the i$ea o" a strati"ie$ ran$om sample# consi$er the"ollowing research pro%lem.

5 researcher wants to stu$y the views o" a group o" si'th"orm stu$ents a%out their e$ucation.

The school they choose to stu$y has B) stu$ents in its "irst year () males an$ *) "emales+ an$B) stu$ents in its secon$ year (1) males an$ H) "emales+.

5 *)7 sample will %e $rawn "rom this target population (* stu$ents+ an$ the views o" 1st

year"emales (*)+ are ?ust as important to the researcher as the views o" *n$year males (1)+.

The pro%lem# there"ore# is how can the researcher %e sure that all possi%le views will %erepresente$ in the sample4

" the researcher use$ a simple ran$om or systematic sample it is possi%le that someminority views ("or e'ample# *n$ year males+ might# at %est# %e un$errepresente$ an$# atworst# not represente$ at all# in the sample. To overcome this pro%lem# there"ore# we nee$to look at the i$ea o" =a sample= in a $i""erent way.

nstea$ o" simply $rawing one sample "rom the target population# why not %reak the target

population $own into the $i""erent groups we want represente$ in the "inal sample4

The o%vious thing to $o in this situation is to $eci$e which groups we want represente$an$ then $raw a num%er o" smaller# representative# samples that can %e com%ine$ to giveus our "inal sample. For e'ample# the views we want represente$ are year 1 males an$"emales an$ year * males an$ "emales.

This gives us "our sampling "rames an$ "our samples to take.

To ensure these samples are representative# we have to choose names "or our sample"rom each in $irect proportion to their representation in the target population. Thus:

2( ,irst and second year students(

To achieve this# we create t#o sampling frames.

,rame 2 consists o" the names o" 56 first yearstu$ents.

,rame 3consists o" the names o" 56 second yearstu$ents.

3( Males and females(

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The first sampling frame(first yearstu$ents+ is split into t#o "urther sampling "rames (males andfemales+.

The second sampling frame(second yearstu$ents+ is also split into t#o"urther sampling "rames (malesand females+.

!e then choose the names "or each sample on a ran$om %asis an$# when this has %een$one# we simply com%ine the "our samples to give us the overall sample we re2uire thatwill %e representative o" the target population.

7ear 8ne

Sample 2consists o" 9 first year males

Sample 3consists o" first year females

7ear T#o

Sample 4consists o" 3 second year males

Sample consists o" 26 second year females(

;riefly e+plain #hy stratified sampling depends on the researcher )no#ing thecharacteristics of the target population sampled(

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( Stratified "uota

This sampling techni2ue is a variation on the strati"ie$ ran$om type o" sampling we8ve ?ust$iscusse$. 5s such# the %asic principles involve$ in the sampling process are e'actly thesame (the $ivision o" the main sample into smaller samples+. There is# however# onema?or $i""erence an$ that comes at the stage when the people in the sample are actuallyselecte$. Rather than selecting people ran$omly# 2uota samples allow the researcher toselect people nonran$omly.

5 %rie" e'ample shoul$ make this i$ea clear.

magine you want to 2uestion people a%out their voting %ehaviour. For the sake o"illustration# you $eci$e your sample will %e strati"ie$ in the "ollowing way:

1. Dy Aen$er:

ales an$ Females.

*. Dy 5ge:

ales 1K B an$ males BHM. NFemales 1K B an$ "emales BHM.

n e""ect# there"ore# you will initially %e con$ucting "our small samples that can then %ecom%ine$ into a sample that is representative o" your target population.

&ou are going inclu$e 1)) people in your sample an$# %ase$ on theirproportions in the target population# you "in$ you nee$ to 2uestion:

) males age$ 1K B

H males age$ BHM) "emales age$ 1K B1H "emales age$ BHM.

These age an$ gen$er strati"ie$ groups are your "our 2uota samples an$ you $eci$e toselect the sample %y going $own to your local shopping centre an$ asking people i" theywoul$ answer 2uestions a%out their voting %ehaviour.

The "irst ) males age$ 1K B that you get to agree to answer your 2uestions are

then inclu$e$ in your sample# as are the other 2uota groups in the proportionsyou8ve $eci$e$ upon.

,nce you8ve "oun$ ) males age$ 1K B who agree to %e in the sample you have

"ille$ your 2uota "or this group an$ $o not nee$ to inclu$e any more men o" this age.

!hen every 2uota has %een "ille$# a sample will have %een $rawn that shoul$ %e

representative o" the target population.



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The main point to note here is that selection "or the sample will not have %een on a trulyran$om %asis (since to %e inclu$e$ you ha$ to %e in the shopping centre on a particular$ay an$ at a particular time+# %ut it shoul$ %e a sample that is =ran$om enough= "orresearch purposes.

The "ollowing outlines some o" the uses an$ limitations o" strati"ie$ ran$om an$ strati"ie$nonran$om sampling.

-ses

1. This type o" sampling ensures that )no#n differencesin the target populationwill %e accurately re"lecte$ in the sample.

n %asic terms# there"ore# we can %e sure that in terms o" the characteristics o" ourtarget population our sample will %e $roadly representative.

*. Strati"ie$ samples $o not have to %e very %ig# since it is possi%le# (using small

samplesthat are care"ully strati"ie$+# to make certain that we have accuratelyre"lecte$ the makeup o" our target population.@. Stratified "uotasamples# in particular# are usually relatively cheap an$ 2uick toconstruct accurately.

Limitations

1. n or$er to strati"y a sample the researcher must have accuratean$ up%to%dateinformationa%out the target population. This is not always availa%le.

*. ven in situations when a researcher has accurate in"ormation a%out the$i""erent groups that makeup the target population it is possi%le that thisin"ormation may %e out%of%date%y the time the research %ase$ on the sample isactually con$ucte$. This is especially true where the sample is large and comple+an$ in situations where the composition o" the target population may changerapidlyan$ consistently.

,or e+ample# where agegroups are use$# these will actually change on a $aily%asis.

@. " you are employing a team o" researchers to help you construct a 2uota sampleyou cannot $e certainthat they correctly place$ everyone in the right 2uota

category. "# "or e'ample# your research assistant cannot "in$ ;1)) men over theage o" BH< to "ill their 2uota# there may %e a temptation to "ill it using men un$erthat age

. The "act that strati"ie$ 2uota sample selection is not truly randommay mean itis not representativeo" atarget population(

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;riefly outline at least t#o ma


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=( Sno#$all &8pportunity' Sampling(

!e looke$ earlier at the i$ea o" nonrepresentative sampling an$ mentione$ %rie"ly thei$ea o" =snow%all= or =opportunity= sampling.

Oust as a snow%all rolling $ownhill gets larger an$ larger as it picksup more snow# a ;snow%all

sample< picksup more an$ more to %e in the sample over time.

!e can now %rie"ly $evelop this i$ea.

t is not always possi%le "or a researcher to get hol$ o" a sampling "rame "or a targetpopulation. This may %e %ecause such a list $oesn8t e'ist or %ecause someone whocontrols access to the list will not release it to a researcher. !hatever the reason# it maystill %e possi%le to construct a sample in a a$ hoc (unsystematic+ way.

5s the name suggests# a snow%all or opportunity sample involves the researcheri$enti"ying someone in the target population who is willing to %e researche$.

This person may then suggests another * or @ people (perhaps more+ who will help.These people# in turn# suggest another * or @ people until# in a relatively short space o"time# the researcher has a sample they "eel they can use in their research.

Clearly# this type o" sampling is not going to pro$uce a sample that is truly representativeo" a target population# %ut it may %e the %est that can %e achieve$ in certain situations.

" you use this type o" sampling in your (pro?ect+ work# please pay care"ul attention to thelimitations o" this techni2ue...

!e can note the "ollowing uses an$ limitations o" this sampling techni2ue.

-ses

1. This type o" sampling ena%les a researcher to construct a sample in situationswhere it woul$ not %e possi%le to $o so using any other sampling techni2ue.

*. t can %e a relatively cheap an$ 2uick metho$ o" sampling.

Limitations

1. The sample is unlikely to %e representative o" a target population.

*. There is no way o" checking whether or not your sample is representative.

@. There is a high likelihoo$ o" a sel"selecte$ sample %eing constructe$ (see%elow: Sampling rrors+.

5( Multi%stage &Cluster' Sampling(

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This "orm o" sampling is usually $one when a target population is sprea$ over a wi$egeographic area.

For e'ample# an opinion poll into voting %ehaviour may involve a sample o" 1)))

people to represent the @H million people eligi%le to vote in a Aeneral lection. " asimple ran$om sample were taken it8s possi%le that the researcher might have to poll1) people in 9ewcastle# 1H people in Car$i""# @ people in Dournemouth an$ so "orth. nother wor$s# it woul$ %e a timeconsuming an$ very e'pensive process an$ the results"rom the poll woul$ pro%a%ly %e outo"$ate %e"ore the poll coul$ %e "inishe$.

To avoi$ these pro%lems# a researcher can use a multistage G cluster sample that

"irstly# $ivi$es the country into smaller units (in this e'ample# electoral constituencies+an$ then into small units within constituencies ("or e'ample# local %oroughs+. Doroughscoul$ then %e selecte$ which# %ase$ on past research# show a representative crosssection o" voters an$ a sample o" electors coul$ %e taken "rom a relatively smallnum%er o" %oroughs across the country.

!e can note the "ollowing uses an$ limitations with this type o" sampling:

-ses

1. This type o" sample saves the researcher time an$ money.

*. ,nce a relatively relia%le sample has %een esta%lishe$# the researcher can usethe same or a similar sample again an$ again (as with political opinion polling+.

Limitations

1. /nless great care is taken %y the researcher it is possi%le that the clustersamples will not %e representative o" the target population.

*. ven though it is a relatively cheap "orm o" sampling# this is not necessarily thecase. 5 sample that seeks to represent the whole o" Dritain# "or e'ample# is stillgoing to %e too e'pensive "or many researchers

>( Multi%phase Sampling(

This type o" sampling $epen$s on a sample o" some $escription alrea$y having %een

taken an$ simply involves the i$ea that the researcher takes a =sample "rom theirsample=. ,ne reason a researcher might want to $o this is to "ollowup any i$eas raise$%y research on the larger sample an$# rather than re2uestion the whole sample asmaller# moreselective# group is chosen to represent the sample o" the target population.

>aving looke$ at the ma?or types o" sampling techni2ues use$ %y sociologists# we cancomplete this unit %y consi$ering two o" the more common "orms o" sampling error that# i"present in our sample# may make them (acci$entally or $eli%erately+ unrepresentative.Sampling *rrors

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2( The Self%Selected Sample(

,ne o" the most common "orms o" sampling error is the creation o" a sample thate""ectively =selects itsel"= rather than %eing selecte$ %y the researcher. n simple terms#rather than the researcher selecting people to appear in a representative sample# peoplechoose# in some way# to %e in the sample. This type o" error is "airly common in =research=that is not very rigorous or systematic in its approach3 "or e'ample# the type o" opinionpolls that appear in newspapers an$ magazines almost invaria%ly involve a sel"selecte$(an$ unrepresentative+ sample. For e'ample:

5 newspaper that asks its rea$ers to respon$ to the 2uestion#

;Should people convicted of murder $e given the death penalty?

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A level Sociology