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A research population is generally a large collection of
individuals or objects that is the main focus of ascientific query.
Sample is a group of people, things, or places where data
are collected.
Sample is a part which represents a population
(A sample is simply a subset of the population.)
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Sample
Thenumber
Themethods
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The minimum number of sample:
Population
< 100
101-500 501-1000
>1000
Sample
50%
30-50% 20-30%
15-20%
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Simple
RandomSampling
Systematic
randomSampling
StratifiedRandomsampling
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1List all names of population
2
Write all names in small pieces of papers, thenroll them
3
Put the rolled papers into a box and shake the
box, so the rolled papers will be mixed.
4
Take the rolled papers one by one until you getthe number of needed sample
A. Raffling
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1 List all names of population
2
Prepare the table of random numbers
3 Close your eyes and tick one number using pencil.
4
Check whether the number you choose is available in thelist of population.
5
Move your pencil up/down/left/right until you get thenumber of needed sample
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1List all names of population
2
Determine the interval by dividing thepopulation with the sample needed
3
Close your eyes and choose one number asyour first sample
4
Determine the next samples based on theinterval which has been counted before.
It is used when the population is arrangedsystematically
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It is used when there are stratification in the
population
e.g. Population of the stratification in senior high
school: grade X, XI, and XII
*grade X, XI, and XII are called
Subpopulation
There are two types of stratified random sampling
A. Proportional Stratified Sampling
B. Disproportional Stratified Sampling
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A. Proportional Stratified Sampling
In determining the sample, we shouldconcern the ratio of each stratum
B. Disproportional Stratified Sampling
In determining the sample, we notconcern about the difference of thenumber of subpopulations member
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In a senior high school, there are 222 studentsof grade X,333 students of grade IX, and444 students of grade IIX, so the total
number of students is 999.
Sample: 30% x 999 = 298
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a. Proportional :
Grade X : 30% x 222 = 67 students
Grade IX : 30% x 333 = 100 studentsGrade IIX : 30% x 444 = 133 students
b. Disproportional :
298/ 3 class = 99 students of each grade
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Random Sampling
- Define the population
- Select the sample
The benefit of random sampling:
It limits the probability that you choose abiased sample.
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Defining the population
- It refers to the establishment ofboundary conditions that specify whoshall be included in or excluded from the
population
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Establishing specification for stratifiedrandom sampling
The use of stratified random sampling will permit
you to include parameters of special interest and
to control for internal validity in terms of selectionfactors trough the use of moderatororcontrol
variable.
Stratification represents a good operationalstrategy forscreening membersof the population
into and out of the study and forreducing the
variability of the sample.
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25%
75%
Two-year colleges in
the U.S.A
Private
Public
10%
15%
15%60%
Two-year colleges in the U.S.A
private, rural
private, urban
Public, rural
public, urban
two-year colleges in the
U.S.A
two- yearcolleges in the
U.S.A
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1%
9%
5%
10%
3%
12%48%
12%
two-year colleges in the U.S.A
private, rural, large
private, rural, small
private, urban, largeprivate, urban, small
public, rural, large
public, rural, small
public, urban, large
public, urban, small
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REMEMBER:
In stratified random sampling, you have more than one subpopulation.
Each subpopulation or stratum have random basis, however all should
be represented in the sample.
E.g. If in the population 65% are male, so in the sample taken should
be 65% male.
Each stratification parameter represent a control variable, that is, a
potential source of error or extraneous influence that may provide an
alternative explanation for the outcome of study.
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Determining sample size
How large a sample should I employ??
Use as small a sample as possible for reason of time and
cost, while keeping it large enough to ensure its
representativeness.
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Representativeness of the sample can be established at an
acceptable level of probability/ confidence level(z).
z is usually set between 90 99:
90 = 90% chance or representativeness (0.10 level) z = 1.65
95 = 95% chance or representativeness (0.5 level) z = 1.9699 = 99% chance or representativeness (0.01 level) z = 2.58
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It is desirable to minimize sampling error in order to maximize
sample representativeness. So that, a researcher should
maintain the same proportion in stratified sampling.
e.g. 50% male and 50% female in the population should be
represented by 50% male and 50% female in the sample.
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Formula:
N= (z/e)2 (p) (1
p)
N = sample size
z = confidence levele = proportion of sampling error in a given situation
p = the estimated proportion
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E. g.
How to count the sample size of Private two-year colleges
account for 25 percent of all two-year colleges, when you
want 95% of confident level (z=1.96) with a tolerable amount
of error no greater than plus minus 10%.
Answer:
N= (z/e)2 (p) (1 p)
N= (1.96/0.10) 2 (0,25) (1 0,25)
N= (19,6) 2 (0,25) (0,75)
N= (384,16) (0,1875)
N= 72,03 => 72
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Thank You