sampling and population

7/30/2019 Sampling and Population

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PREPARED BY:

NOORHANANI BT MAMAT @ MUHAMMAD2012599003

EDU 702(RESEARCH METHODS IN EDUCATION)


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POPULATIONDefinition:-

Refers to all members of a particular group.

The group of interest to the researcher

The group to which the results will be applied

(Fraenkel, Wallen, Hyun, 1990)

The larger group from which individuals are selected toparticipate in a study

The total number of persons inhabiting a country, city, or

any district or area. (Dictionary.com, 2012)


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SAMPLE

Any part of a population of individuals on whom information is

obtained

A group on which the population is obtained


The representatives selected for a study whose characteristicsexemplify the larger group from which they were selected.

(Richard M. Jacobs, OSA, PhD,)


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POPULATION AND SAMPLE

Example:-

i) A researcher is interested in studying the effect of the

implementation of LINUS 2.0 in Primary School in

Terengganu

PopulationAll the English teachers of Primary school in

Terengganu (370 )

Sample - 20 selected English teacher from each

district. (8 x 20=160)


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POPULATION AND SAMPLE Note:

In the same group , they can be a sample and a

population in different context.

Example,

All the English teacher in Terengganu constitute the

population of English teacher in Terengganu , yet they

also constitute a sample of all English teacher in Malaysia.


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POPULATION AND SAMPLE Sometimes the population from which the sample is drawn may

not be the same as the population about which we actually want

information.

Large gap but not overlap

Sometimes they may be entirely separate

Example:-

Study rats in order to get a better understanding of human

health,

Study records from people born in 2008 in order to make

predictions about people born in 2009.


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POPULATION AND SAMPLE

SAMPLE

POPULATION

INFERENCE


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SAMPLING

The process of selecting a number of individuals for a study in

such a way that the individuals represent the larger group from

which they were selected (Richard M. Jacobs, OSA, PhD, )

The process of selecting units (e.g., people, organizations) from

a population of interest so that by studying the sample we may

fairly generalize our results back to the population from which

they were chosen

(William M.K Trochim, 2006)


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OBJECTIVES OF SAMPLING

To make inferences about the larger population

from the smaller sample.

To gather data about the population in order to

make an inference that can be generalized to the

population



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ADVANTAGES OF SAMPLING Saves money , time and energy

Provides information that is almost as accurate as that obtained from a

complete census

Possible to obtain more detailed information from each unit of the sample

The only means available for obtaining the needed information when the

population appears to be infinite or is inaccessible

Has much smallernon-response, much easier.

Essential to obtaining the data when the measurement process physicallydamages or destroys the sampling unit under investigation.

Extensively used to obtain some of the census information.

Provides a valid measure of reliability for the sample estimates


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DISADVANTAGES OF SAMPLING Mostly can be biased and in some cases can

choose people/units inappropriate for the

circumstances


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MISTAKES TO BE CONSCIOUS OF

Threaten to render a studys findings invalid

Sampling Error

Sampling Bias



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SAMPLING ERROR

The chance and random variation in variables that

occurs when any sample is selected from the population

To avoid sampling error, a census of the entire population

must be taken

To control for sampling error, researchers use various

sampling methods



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SAMPLING BIAS

Nonrandom differences, generally the fault of the

researcher

Cause the sample is over-represent individuals orgroups within the population

Lead to invalid findings

Sources of sampling bias include the use of volunteers

and available groups



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STEPS IN SAMPLING

1. Defining the population (N)

2. Determine sample size (n)

3. Control for bias and error

4. Select the sample


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DEFINE THE POPULATION (N)

Identify the group of interest and its characteristics to

which the findings of the study will be generalized

Choose the target population

The ideal selection- Actual population

The accessible or available population must be used

The realistic selection



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TARGET VERSUS ACCESSIBLE

POPULATIONS

TARGET ACCESSIBLE

1. Rarely available to generalize 1. Able to generalize

2. Researchers ideal choice 2. Researchers realistic choice3. Example:

All Year 1 and Year 2 pupilsin Terengganu

3. Example:All Year 1 and Year 2 in SKAlor Peroi, Besut, Terengganu.


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Remember Narrow population- Save time, effort and money

Generalizability is limited

The population and sample must be specific enough

provide readers a clear understanding of the applicability of our studyto their particular situation and their understanding of that same

population.

Common weaknesses of published research report-

fail to define in detail

Actual sample may be different from original-

Subject refuse to participate, drop out, data lost and etc



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DETERMINE THE SAMPLE SIZES

The size of the sample influences both the

representativeness of the sample and the statistical

analysis of the data

Larger samples are more likely to detect a difference

between different groups

Smaller samples are more likely not to be

representative



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RULES TO DETERMINE SAMPLE SIZES

The larger the population size, the smaller the percentage of

the population required to get a representative sample

For smaller samples (N 100), there is little point in sampling.

Survey the entire population

If the population size is around 500, 50% should be sampled.

If the population size is around 1500, 20% should be sampled. .

Beyond a certain point (N = 5000), the population size is almost

irrelevant and a sample size of 400 may be adequate.



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RULES TO DETERMINE SAMPLE SIZES Minimum numbers of subject needed


STUDIES MINIMUM NUMBERS

DESCRIPTIVE 100

CORRELATIONAL 50

EXPERIMENTAL AND

CAUSAL-COMPARATIVE

30 PER GROUP

QUALITATIVE 1-20


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CONTROL FOR BIAS AND ERROR

Be aware of the sources of sampling bias and identify

how to avoid it

Decide whether the bias is so severe that the results of

the study will be seriously affected

In the final report, document awareness of bias, rationale

for proceeding, and potential effects



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SELECT THE SAMPLE

A process by which the researcher attempts to ensure that the

sample is representative of the population from which it is to be

selected

Requires identifying the sampling method that will be used



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SELECT THE SAMPLETwo types of sampling

Random sampling

Non random sampling


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RANDOM SAMPLING Allows a procedure governed by chance to select the sample;

controls for sampling bias

Every members of the population had equal chances to be

selected

A group of individual represent the entire population

An accurate view of the larger group

Example: 100 students names were place into a box, mixed them thoroughly

and then draws out 25 students name



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RANDOM SAMPLING Any method of sampling that utilizes some form ofrandom

selection.

In order to have a random selection method, you must set up

some process or procedure that assures that the different units

in your population have equal probabilities of being chosen

Use computers as the mechanism for generating random

numbers as the basis for random selection.



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RANDOM SAMPLING METHODS

Simple Random Sampling

Stratified Random Sampling

Cluster Random Sampling

Two Stage Random Sampling


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RANDOM SAMPLING METHOD

The process of selecting a sample that allows individual in the

defined population to have an equal and independent chance

of being selected for the sample

E.g.. Obtain 200 samples from 2000 subject by using a table.

Best way to obtain sample representatives in larger population

Table of random number-

An extreme large list of numbers that has no order or pattern



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STEPS IN RANDOM SAMPLING METHOD1. Identify and define the population

2. Determine the desired sample size.

3. List all members of the population

4. Assign all individuals on the list a consecutive number from zero to the

required number.1. Each individual must have the same number of digits as each other

individual.

5. If the number corresponds to the number assigned to any of the

individuals in the population, then that individual is included in the

sample.

6. Go to the next number in the column and repeat step #7 until the

desired number of individuals has been selected for the sample.



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ADVANTAGES AND DISADVANTAGE

Advantages

Large- likely to produce a representative sample

Easy to conduct

Strategy requires minimum knowledge of the population to be sampled

Disadvantage

Not easy to do

Need names of all population members

May over- represent or under- estimate sample members

There is difficulty in reaching all selected in the sample


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STRATIFIED RANDOM SAMPLING

Process which certain subgroup (strata) selected for the

sample in the same proportion that they exist in the

population.

E.g.. The proportion of gender as same as in population (percentage)

Dividing your population into homogeneous subgroups and

then taking a simple random sample in each subgroup

Objectives

Divide the population into non-overlapping groups (i.e.,strata)


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STEPS IN STRATIFIED RANDOM SAMPLING1. Identify and define the population

2. Determine the desired sample size

3. Identify the variable and subgroups (strata) for which you want to

guarantee appropriate, equal representation.

4. Classify all members of the population as members of one identified

subgroup.

5. Randomly select, using a table of random numbers) an appropriate

number of individuals from each of the subgroups, appropriate

meaning an equal number of individuals



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ADVANTAGES AND DISADVANTAGE Advantages

More precise sample

Can be used for both proportions and stratification sampling

Sample represents the desired strata

Disadvantages

Need names of all population members

There is difficulty in reaching all selected in the sample

Researcher must have names of all populations


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CLUSTER RANDOM SAMPLING

The process of randomly selecting intact groups, not

individuals, within the defined population sharing similar

characteristics

E.g.. Population of 10,000 teachers, 10 school were as a sample. All

the teachers in 10 schools are sample.

More effective with larger numbers of cluster

Similar to simple random sampling

Sampling unit is a group and not the individuals.


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STEPS IN CLUSTER RANDOM SAMPLING

1. Identify and define the population

2. Determine the desired sample size.

3. Identify and define a logical cluster.

4. List all clusters (or obtain a list) that make up the populationof clusters.

5. List all clusters (or obtain a list) that make up the populationof clusters.

6. Determine the number of clusters needed by dividing thesample size by the estimated size of a cluster

7. Randomly select the needed number of clusters by using atable of random numbers.

8. Include in your study all population members in eachselected cluster.


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ADVANTAGES AND DISADVANTAGE

Advantages

Efficient

Researcherdoesnt need names of all population members Reduces travel to site

Useful for educational research

Disadvantage

Fewer sampling points make it less like that the sample is

representative


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Combination of Cluster Random Sampling and

Individual Random Sampling

E.g.. Population 3000 individuals in 100 classes

Selecting 25 class

Randomly select 4 students from each class

Less time-consuming

TWO STAGE RANDOM SAMPLING


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NONRANDOM SAMPLING

Nonprobability- purposive sampling

Does not have random sampling at any state of the

sample selection; increases probability of sampling bias

Each member did not have equal chance of being selected

Example: Each person who enters the bookstore in lunch time will be given a

questionnaire. (anonymous)

After two weeks, they got 200 completed questionnaire


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NONRANDOM SAMPLING

METHODS

Systematic Sampling

Convenience Sampling

Purposive Sampling


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SYSTEMATIC SAMPLING

The process of selecting individuals within the defined

population from a list by taking every nth name.

E.g.. Random Start

Population- 5000 names

Selecting every tenth name on the list till it reach 500

sample

Two term

Sampling interval

Sampling ratio


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SYSTEMATIC SAMPLING Sampling Interval

Distance in a list between each of the individuals selectedfor sample

Population size________________

Desired sample size

Sampling Ratio Proportion of individuals in the population that is selected

for the sampleSample size

________________Population size


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STEPS IN SYSTEMATIC SAMPLING

1. Identify and define the population.

2. Determine the desired sample size

3. Obtain a list of the population

4. Determine what n is equal to by dividing the size of the population by the

desired sample size.

5. Start at some random place in the population list. Close you eyes and

point your finger to a name.

6. Starting at that point, take every nth name on the list until the desired

sample size is reached. If the end of the list is reached before the desired

sample is reached, go back to the top of the list.


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ADVANTAGES AND DISADVANTAGES

Advantage

Sample selection is simple

Disadvantage

All members of the population do not have an equal chance of

being selected

The Nth person may be related to a periodical order in the

population list, producing un-representativeness in the sample

Periodicity- a markedly biased sample can result

If the arrangement of individuals on the list is in some sort of

pattern accidentally coincidence with the sampling interval.


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SYSTEMATIC SAMPLING

When planning

Ensure no cyclical pattern

Not bias the sample


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CONVENIENCE SAMPLING

The process of including whoever happens to be available at

the time

Called accidental orhaphazard sampling

E.g.. Restaurant Manager select 50 samples by choosing the

first 50 students who walk in front of his store.

Cannot be considered as sample-

Should be avoid

Should be replicated to decrease the like-hood that the results

obtained were simply one time occurrence.


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ADVANTAGE AND DISADVANTAGE

Advantage

Convenience

Disadvantage

Bias


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PURPOSIVE SAMPLING

The process whereby the researcher selects a sample based on

experience or knowledge of the group to be sampled

Use personal judgment to select sample

Suit or not to be a sample

E.g..

1)Teacher choose 2 students from each level of intelligent to find

about how does her class feel about the role play in the classroom

2) Researcher only interview those he think possess the needed

information.


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PURPOSIVE SAMPLING

Disadvantage

Researchers judgment maybe in error

Not be correct in estimating the representativeness and expertise


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GENERALIZING FROM A SAMPLE Generalize

Apply the findings of a particular study to people/ setting

that go beyond the particular people / settings used in

study

Considering nature and environmental condition

Determine the External Validity

The extent to which the result of a study can be generalized

from a sample to a population


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GENERALIZING FROM A SAMPLE

Population Generalizability

The extent to which the results of a study can be generalized to

the intended population

Result of investigation need to be applicable as wide as possible

Representativesrelevant

Contributing factor to any result obtain

The sample must include allstudents and teacher Not applicable when

The result is for particular group at particular time

All members are included


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GENERALIZING FROM A SAMPLE Sample - As thoroughly as possible

To let others judge it well

Representatives of the target population

Replication

Repeat the study using different groups in different situation

Get same result- additional confidence in generalizing

finding


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GENERALIZING FROM A SAMPLE Ecological Generalizability

The extent to which the results of a study can be

generalized to conditions or settings other than those that

prevailed in a particular study

Ensure the nature of environmental conditions same in all

important respects in any new situation


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THANK YOU

sampling and population

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