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CHAPTER 7SAMPLING DESIGN
7.1 REASONS FOR SAMPLING
7.2 SAMPLE SIZE DECISION
7.3 SAMPLING METHOD
7.4 ERRORS IN SAMPLING
SAMPLING
SAMPLING
The process of selecting a sufficient number of elements from the
population, so that results from analyzing the sample are
generalizable to the population.
REASONS FOR
SAMPLING
Less cost
Less errors due to less
fatigue
Less time
Destruction of elements
avoided
SAMPLE SIZE DECISION
There are variety sample size decision that available . The choice can be defend on the following: Population The element Population frame Sample Sampling unit The subject
SAMPLE SIZE DECISION
a) Population -Refer to the entire group of people, events or
things of interest that the population that the researches wishes to investigate.
b) Element - Single member of the population. The census
is a count of all elements in the human population.
c) Population frame - the listing of all the element in the
population from which the sample is drawn. It is also known as sampling frame.
SAMPLE SIZE DECISION
d) Sample -Subset of the population. It is a
subgroup of the population selected using sampling method or design.
e) Sampling unit -the element or set of the elements that
is available for selection in some stage of the sampling process.
f) Subject -a subject is a single member of the
sample.
The sampling process
Define the population
Determine the sample
frame
Determine the sampling design
Determine the appropriate sample size
Execute the sampling process
Sample Size
Most research
• > 30 < 500 are appropriate
Sub-samples
• Min 30 for each category
Multivariate research
• At least 10 times more than the number of variables
Experimental research
• Can be low as 10 to 20
Sample size
Precision• How close the estimate to
the true population characteristics with low margin of error
Confidence
•How certain the estimate will really hold true for the population.•Commonly accepted confidence level ≤0.05 (95% confidence)
Population
Defined in terms Elements
Geographical
Boundaries & Time
Sample Frame
Physical representation of all the elements in the population from which the sample is drawn
Make sure that sample frame the latest and most up-to-date to avoid coverage error
Sampling DesignTarget population
of focus to the study
The exact parameters need to be investigated
Availability of sampling frame
Sample size needed
Costs associated to the sampling
design
Time frame available for
data collection
Sampling Design
Probability
sampling
Non-probabili
ty sampling
SAMPLING TECHNIQUES
Probability SamplingSimple Random Sampling
Systematic Sampling
Stratified Random Sampling
Cluster Sampling
Simple Random Sampling
PROCEDURE– Each element has a known
and equal chance of being selected
CHARACTERISTICS– Highly generalizable
– Easily understood
– Reliable population frame necessary
Systematic Sampling
PROCEDURE– Each nth element, starting with
random choice of an element between 1 and n
CHARACTERISTICS– Easier than simple random
sampling– Systematic biases when
elements are not randomly listed
Cluster Sampling
PROCEDURE
– Divide of population in clusters– Random selection of clusters– Include all elements from selected clusters
CHARACTERISTICS
– Intercluster homogeneity– Intracluster heterogeneity– Easy and cost efficient– Low correspondence with reality
Stratified SamplingPROCEDURE– The process of dividing
members of the population into homogeneous subgroups before sampling
– There are two types of stratified random sampling:• Proportionate
Stratum A B C
Population size 100 200 300
Sampling fraction 1/2 1/2 1/2
Final sample size 50 100 150
CHARACTERISTICS– Interstrata heterogeneity– Intrastratum homogeneity– Includes all relevant
subpopulations
•DisproportionateStratum A B C
Population size 100 200 300
Sampling fraction 1/2 ¾ 1/3
Final sample size 50 150 100
Nonprobability Sampling
Convenience Sampling
Judgment Sampling
Quota Sampling
Members of the population are chosen based on their relative ease of access.
The researcher chooses the sample based on who they think would be appropriate for the study.
A quota is established (say 65% women) and researchers are free to choose any respondent they wish as long as the quota is met.
5 Common Sampling Errors
oPOPULATION SPECIFICATION ERROR
oSAMPLE FRAME ERROR
oSELECTION ERROR
oNON-RESPONSE
oSAMPLING ERRORS
Measurement of Variables
Operational definition Scales
One lends itself to objective and precise
measurement;The other is more
nebulous and does not lend itself to accurate
measurement because of its abstract and
subjective nature.
Type of variables
Object – house, countries, restaurants.
Examples of characteristics of
objects are arousal seeking tendency,
achievement motivation,
organizational effectiveness
(Characteristics of) Objects
the assignment of numbers or other
symbols to characteristics (or
attributes) of objects according to a pre-specified
set of rules.
Measurement
26
Operationalizing Concepts
Operationalizing concepts: reduction of
abstract concepts to render them
measurable in a tangible way.
Operationalizing is done by
looking at the behavioural dimensions,
facets, or properties denoted by
the concept.
Example
27
ScaleTool or mechanism by which individuals are
distinguished as to how they differ from one
another on the variables of interest to our study.
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4 TYPES OF
SCALES
Nominal Scale• A nominal scale is one that allows the
researcher to assign subjects to certain categories or groups.
• What is your department?O Marketing O Maintenance
O Finance O Production O Servicing
O Personnel O Sales O Public Relations O Accounting
• What is your gender?O MaleO Female 30
Ordinal Scale
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Ordinal scale: not only categorizes variables in such a way as to denote differences among various categories, it also rank-orders categories in some meaningful way.
What is the highest level of education you have completed?
O Less than High School O High School O College Degree O Masters Degree O Doctoral Degree
Interval Scale• Interval scale: whereas the
nominal scale allows us only to qualitatively distinguish groups by categorizing them into mutually exclusive and collectively exhaustive sets, and the ordinal scale to rank-order the preferences, the interval scale lets us measure the distance between any two points on the scale.
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• Circle the number that represents your feelings at this particular moment best. There are no right or wrong answers. Please answer every question.
1. I invest more in my work than I get out of it
I disagree completely 1 2 3 4 5 I agree completely
2. I exert myself too much considering what I get back in return
I disagree completely 1 2 3 4 5 I agree completely
3. For the efforts I put into the organization, I get much in return
I disagree completely 1 2 3 4 5 I agree completely33
Ratio scale
• Indicates not only the magnitude of the differences but also their proportion.
THE END!!!
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