Transcript Link to Powerpoint Slide Presentation on Types of Sampling

Types of Sampling
Simple Random
Cluster
Stratified
Systematic (every kth element is sampled)
Assumptions
Members of the Population can be
numbered from 1 to N where N is the
population size
You have a mechanism for randomly
picking n numbers (usually without
replacement) from the collection of
numbers 1,2,3,…,N
If number k is selected, the population
element with that number is in the sample
Simple Random Sample
Population
above right
In a Simple
Random
Sample each
population
member is
equally likely to
be selected
Click to sample
1
6
12
2
3
4
5
17
18
8
13
14
10
9
16
7
15
20
19
11
21
Cluster Sampling
The Population (right)
can be divided into
strata
A stratum consists of
population elements
that are similar in
some way
All of one or more
strata are randomly
selected and used in
the sample—see next
slide
1
13
2
14
12
4
17
3
5
8
6 7
24
9
11
10
15
16
22 21
19 23 20
18
Population Above—Click to take a
Cluster Sample
1
2
12
4
3
5
8
6
13
7
10
9
11
14
17
15
24
16
22
19 23 20
21
18
Stratified Sampling
The Population (right) can
be divided into strata
A stratum consists of
population elements that
are similar in some way
A random sample from
each stratum is randomly
selected and used in the
sample—see next slide
1
13
2
14
12
4
17
3
5
8
6 7
24
9
11
10
15
16
22 21
19 23 20
18
Population Above—Click to take a
Stratified Sample
1
2
12
4
3
5
8
6
13
7
10
9
11
14
17
15
24
16
22
19 23 20
21
18
Systematic (every kth)
A starting number is randomly chosen
The population element corresponding to
the starting number and every kth
population element after that are selected
for the sample
‘Circular’ counting is used
Every 7th Element Sample
Population
above right
Click once to
get a random
starting
element
Click again to
get every 7th
element after
that
1
6
12
2
3
4
5
17
18
8
13
14
10
9
16
7
15
20
19
11
21