•
Distinguish between a meta-analysis and
a case study.
•
Distinguish between observational studies
and experimental studies.
•
Learn the basic techniques for choosing a
sample.

40
Process of a Study

41
Observational Studies
•
An
observational study
observes data that
already exists.
•
No manipulation of the sample is performed by
the researchers.
•
No cause-effect relationships can be determined
between variables.
–
For example, if we collect data on SAT scores and the
GPA of freshmen college students, we might find a
relationship between the variables, but it would be
inappropriate to conclude a cause and effect
relationship.

42
Observational Studies
•
A researcher collects data from a
sample
of the
population
.
•
A
representative sample
is one that as the
relevant characteristics as the population and
does not favor one group of the population over
the other.
•
In choosing a sample, we need a
sampling
frame
which is list of all members of the
population from which a sample can be drawn.

43
Observational Studies
•
There are several basic methods of choosing a
sample
from a
population
.
•
If the goal is to collect information from a representative
sample, the best one we could find is the entire
population.
•
Gathering data from every member of the population is
called a
census
.

44
Observational Studies
•
A census is impractical because of the
following reasons:
–
It can be too time consuming.
–
It can be too expensive.
–
Also, the data collection could be destructive
in nature.

45
Random Sampling
•
A
random sample
is one in which every member
of the
population
has an equal chance of being
selected.
•
Random sampling can be performed using the
following methods:
–
Writing names on pieces paper, put the pieces of
paper in hat and drawing names at random from the
hat.
–
Assigning numbers to names and using a random
number table or a random number generator to select
the sample.

46
Random Sampling

47
Stratified Sampling
•
A
stratified sample
is one in which members of
the population are divided into two or more
subgroups, called
strata
, that share similar
characteristics like age, gender, or ethnicity.

48
Stratified Sampling
•
The separate samples from the different
strata do not need to be the same size.
•
The total sample could be drawn so that
the proportion from each strata reflects the
composition of the population.

49
Cluster Sampling
•
A
cluster sample
is one chosen by dividing the population
into groups, called
clusters
, that are each similar to the
entire population. The reseacher then randomly selects
some of the clusters.
•
The
sample
consists of the data collected from
every
member of each
cluster
selected.

50
Systematic Sampling
•
A systematic sample is one chosen by selecting
every
n
th
member of the population.

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- Fall '18
- F. TAILOKA
- researcher, observational studies