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
(Fraenkel, Wallen, Hyun, 1990)
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
(Richard M. Jacobs, OSA, PhD,)
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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
(Richard M. Jacobs, OSA, PhD,)
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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
(Richard M. Jacobs, OSA, PhD,)
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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
(Richard M. Jacobs, OSA, PhD,)
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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
(Richard M. Jacobs, OSA, PhD,)
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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
(Fraenkel, Wallen, Hyun, 1990)
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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
(Richard M. Jacobs, OSA, PhD,)
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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.
(Richard M. Jacobs, OSA, PhD,)
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RULES TO DETERMINE SAMPLE SIZES Minimum numbers of subject needed
(Fraenkel, Wallen, Hyun, 1990)
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
(Richard M. Jacobs, OSA, PhD,)
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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
(Richard M. Jacobs, OSA, PhD,)
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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
(Fraenkel, Wallen, Hyun, 1990)
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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.
(Richard M. Jacobs, OSA, PhD,)
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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
(Fraenkel, Wallen, Hyun, 1990)
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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.
(Richard M. Jacobs, OSA, PhD,)
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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
(Richard M. Jacobs, OSA, PhD,)
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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
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