Sampling Pre

7/27/2019 Sampling Pre

1/32

SAMPLING


2/32

The Sampling Design Process

Define the Population

Determine the Sampling Frame

Select Sampling Technique(s)

Determine the Sample Size

Execute the Sampling Process


3/32

Population

The target population is the collection of elements or objectsthat 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 thesampling process.

Extent refers to the geographical boundaries.

Time is the time period under consideration.
http://www.picsearch.com/info.cgi?pl=en&act=intr&id=106897753&q=sampling&opt=&back=search%2Ecgi%3Fq%3Dsampling%26start%3D%31%31%32%26


4/32

Sample

Sampling

Process of separating the representative part from populationis 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 ofpopulation
http://www.picsearch.com/info.cgi?pl=en&act=intr&id=106897753&q=sampling&opt=&back=search%2Ecgi%3Fq%3Dsampling%26start%3D%31%31%32%26


5/32

Population Size: Total number of elements in population

Element:Individual member of population

Sample:Representative part of the population

Sample frame:A list of elements from which the sample isactually drawn

Sample Size: Total number of elements selected frompopulation.Subject:Individual member of sample

Respondent: Who answers the query.


6/32

Categorization of Sampling method

There 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 becomethe part of the sample.

Non probability based:

In non-probability based sampling methods each and everymember from the population does not get an equal chance

of being selected in the sample.


7/32

Sampling

Probability

Simple Random stratifiedcluster

nonsystematic

Proportionatesystematic

Disproportionate

size variance

Non Probability

quota

snowball

judgment

convenience


8/32

Probability based sampling methods

Sampling procedure in which each and

every element of population has a fixedprobabilistic chance of being selected

for the sample.


9/32

Probability

Simple Random stratifiedcluster

nonsystematic

Proportionatesystematic

Disproportionate

size variance


10/32

Simplerandom Sampling Method

With simple random sampling, the

probability of selection into the sample

is known and equal for all members

of population. Sample is selected in sucha way that every element of the

population has a known and equal

chance of being chosen for the sample.

Also called random sample. The sampleis selected from the entire population i.e.

without dividing respondents into

groups.


11/32

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

Nonsystematic:

This implies that every number is selected independently of

every other element. This method is equivalent to a lottery

system.

Eg: A lucky draw.


12/32

Stratified Sampling Method

A 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.


13/32

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 thatexists in a group. More the difference

more you select, the less the

difference less you select.
http://www.animationfactory.com/animations/animals/monkeys/54bd6/http://www.animationfactory.com/animations/animals/monkeys/16f821/


14/32

Steps Involved in Stratified Sampling

1. 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 simplerandom sampling method
http://www.animationfactory.com/animations/people_m_z/miscellaneous/1354bd/


15/32

Total Population

Male

Female

60 students

10%

40 students

10%

100 students: 10%

6

4

10

Selecting Numbers of Respondents by Proportionate

Proportionate ( Size )

Larger the size of the group the more we select, the smaller

the size of strata the less we select.

Strata-1

Strata-2


16/32

Selecting Numbers of Respondents by Proportionate

Proportionate ( Variance )

More the difference in a group more we select the less the

differences in a group the less we select.

Total Population

Male

Female

60 students

40 students

100 students3

6

d

dd

Here 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 achieved

Strata-1

Strata-2


17/32

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 desiredsample size according to your judgment

about the importance of the strata in the

research.


18/32

Total Population

Male

Female

60 students

40 students

100 students

In this type the Respondent are selected on the Judgment

of the Researcher. Researcher decide which group is more

important

5

5

Here the researcher thinks that both the strata

are equally important for the research.

Strata-1

Strata-2


19/32

Cluster Sampling Method

Population is divided into internally heterogeneoussubgroups. 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.


20/32

Cluster ( Area Sampling Method )DHA

DHA

Phase 1

DHA

Phase 2

DHA

Phase 3

DHA

Phase 4

Street 1 Street 2 Street 1 Street 2 Street 1 Street 2 Street 1 Street 2

Khayaban Khayaban Khayaban Khayaban


21/32

Non probability based Sampling

methods

In non-probability based sampling

methods each and every member fromthe population does not get the equal

chance of being selected in the sample.

It rely on the personal judgment orconvenience of the researcher.
http://www.animationfactory.com/animations/people_m_z/miscellaneous/135365/


22/32

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 respondentstotally to the field researcher, with no quotas or qualifications

imposed. It consists of those units of the population that are

easily accessible.
http://www.animationfactory.com/animations/people_m_z/miscellaneous/135365/http://www.picsearch.com/info.cgi?pl=en&act=intr&id=130333387&q=judgement&opt=&back=search%2Ecgi%3Fq%3Djudgement%26start%3D%34%38%26


23/32

Judgment

Judgement sampling is a form of non-

probability sampling in which thepopulation elements are selected based

on the judgment of the researcher.

In judgment sampling researcher useshis/ her own educated guess or

judgment to identify who will be in

the sample.
http://www.picsearch.com/info.cgi?pl=en&act=intr&id=130333387&q=judgement&opt=&back=search%2Ecgi%3Fq%3Djudgement%26start%3D%34%38%26http://www.picsearch.com/info.cgi?pl=en&act=intr&id=33812219&q=snow%20ball&opt=&back=search%2Ecgi%3Fq%3Dsnow%25%32%30ball%26start%3D%33%32%26


24/32

Snow ball

Snowball 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 andso 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.
http://www.picsearch.com/info.cgi?pl=en&act=intr&id=33812219&q=snow%20ball&opt=&back=search%2Ecgi%3Fq%3Dsnow%25%32%30ball%26start%3D%33%32%26


25/32

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 size


26/32

Quota sampling may be viewed as two-stage restricted

judgmental sampling.

The first stage consists of developing control categories,or quotas, of population elements.

In the second stage, sample elements are selected

based on convenience or judgment.

Population Sample

composition composition

Control

Characteristic Percentage Percentage Number

SexMale 48 48 480

Female 52 52 520

____ ____ ____

100 100 1000


27/32

Strength and weakness of sampling techniques

Convenience

Sampling

Judgmental

Sampling

Quota

sampling

Snow Ball

sampling

strength weakness

Least expensive, least time

consuming, most convenient

Selection biasness, sample is

not representative of (P)

Low cost, convenient , less

time consuming

Doesnt allow generalization,

subjective instead of objective

Sample can be controlled

from certain characteristics.

Selection bias, no assurance

of representative.

Can estimate rare

characteristics

Time consuming


28/32

Strength and weakness of sampling techniquesStrength Weakness

Easily understood,results are

projectable

Difficult to construct sampling

frame, expensive, lower

precision, no assurance of

representative

Can increase representativeness, easier to implement, than

Srs, Sampling frame not

necessary.

Can decrease representative

Includes all important

subpopulation, precision.

Difficult to select relevant

stratification variable,expensive,not feasible to

verify many variables.

Cost effective ,

easy implement

Low statistical efficiency

Simple

Random

Systematic

sampling

Stratified

sampling

Cluster

sampling


29/32

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


30/32

Factors to determine sample size

1. Cost2. Time

3. Importance of decision4. Reliability requirements5. Population size6. Nature of the problem

7. Diversity of population

S l Si U d i R h


31/32

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 (percommercial or ad tested)

150 200-300

Test-market audits 10 stores 10-20 stores

Focus groups 2 groups 4-12 groups

T


32/32

T

H

E

EN

D

Sampling Pre

Documents

Transcript of Sampling Pre