Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Presentation sampling
1. EDU 702 :Research Methodology
Sampling
Adibah Halilah bt Abdul Mutalib
1
2. Topic areas:
Definition
• Population
• Sample
Identify & Contrast
• Target and Accessible population
• Random Sampling and Non-Random
Random Sampling
• Types of Random Sampling.
• How to select a random sample.
2
3. Problem :
Relationship
between stress
levels and smoking
among university
students
3
4. Research question : You would like to know the number of
cigarettes the average university students smokes
Population of all university students
in Malaysia = 12,000
Population of university students in
UITM = 4,000
Population of male students = 1,400
10% Populations of UITM first year
male students = 140
4
5. Definition of a Sample
• A small group of people
studied to collect information
Sample to draw conclusion about the
larger group
• Process of selecting the
people (individuals) to be
Sampling observed ( studied)
5
6. Example of sample within a population
Sample:
information
obtained
Population:
results of
studies applied
here
70
700
6
7. Questions: Can a Sample & Population
have the same groups of people?
Smokers at
University
All smokers Sample – Year 1
university students who
are smokers
Population – Smokers at
University
7
8. Discussion: How to select Sample?
Effects of eating “Nasi Lemak” for
breakfast on young students.
Teachers view about teaching Math
and Science in Bahasa Malaysia.
Students addiction to computer
games and poor grades.
8
9. How to define the population
Stage 1: Define the population
• Who can you administer the results to?
• Any size
• Need to have at least one characteristic
different from other population
Stage 2 : Identify “Who” or
“What”
• Educator
• Object
9
10. TARGET vs. ACCESSIBLE POPULATION
• Ideal group/actual group
TARGET researchers like to generalize
• Rarely available
• Those who researchers are
ACCESSIBLE able to generalize
• Actual choice
10
12. Random vs. Non-random-Sampling
Random Non-Sampling
(Purposive)
All have equal and Chosen based on a criteria
independent chance
Selects a representative of No equal chance
population
Should be large and random Some have no chance at all
No bias Some types show biasness
12
13. Random Sampling Methods
(A) Simple Random Sampling
(B) Stratified Random Sampling
(C) Cluster Random Sampling
(D) Two-stage Random Sampling
13
14. (A) Simple Random Sampling ( 1 of 2)
• Each individual has equal and independent
chance of selection
• The larger the sample, the more it represents
the population
• Any differences is not due to biasness
14
15. Simple Random Sampling (2 of 2)
• Method of finding individuals :
Use a table of Choose any Read the numbers
random numbers number on the to select your
( statistic book) column sample
15
16. Using the Table of Random Numbers
• Step 1: Select column of numbers
• Step 2: Choose any number on the column
• Step 3: Read the first 4 digits ( if you have
population of 4 digits)
• Step 4: Pick out numbers and write them
down.
16
17. Exercise: Select the first 30 numbers
for a population of 300.
Column 1 Column 2 Column 3 Column 4
099922 231100 182203 012030
122331 334444 092010 231102
644632 088765 001220 120301
162311 755664 005440 909201
234577 112344 194020 718291
344666 412346 230440 503813
092303 080902 210490 120311
009330 006102 530209 301020
230420 003233 409201 015663
17
19. (B) Stratified Random Sampling
• Certain ‘strata’ selected
• Sample in same proportion as they exist in the
population
• Advantages: Increases likelihood of
representativeness
19
20. Calculating Stratified Random
Sampling
• Step 1: Identify the target ( accessible)
population
• Step 2: Select the ratio of their relationship
• Step 3: Determine the % of target population
used as sample
• Step 4: Calculate the % sample for each strata
• Step 5: Use Table of random numbers to find
the individuals in the respective strata
20
21. Select gender individuals as they exist
in the population ( 365)
Female Male
• 60 % • 40%
• 60 % of 365 = 219 • 40 % of 365 = 146
Therefore, Female : Male
60 : 40
219 : 146
Now, select 40 % of each strata as you
representative…
Female : Male
88 : 58 21
22. (C ) Cluster Random Sampling
• Ideal to include certain groups/ cluster
• However at times it is not possible to select
individual due to
• Time
• Effort
• Select individuals based on ( not individuals)
• Groups
• Clusters
• Subjects
22
23. All Year 6 students in Selangor
Selected schools
chosen as clusters
1 2
6
5
9 3
8 7
11 1 4
10
12 13
23
25. Common mistake made with Cluster
random sampling.
• Randomly selecting only one cluster as a
sample and choosing to interview/ survey all
• Cluster must be randomly selected not
individuals
25
26. (D) Two-stage Random Sampling
• Combination of Cluster random sampling and
individual random sampling
– First select clusters randomly
– Then select students randomly from the clusters.
NH KJ XT
FD
XT
PO PO P, T, S
AB
RS
RS
26