Concepts, relationships, and types of samples are presented. Cases to practice sampling are included. Sample size is also discussed.

1. How
to
Choose
a
Sample
for
Your
Thesis
or
Dissertation

2. Concepts
to
Know
Research
Popula.on
The
whole
set
of
units
(people,
groups,
events,
se4ngs,
etc.)
on
which
the
research
is
focused
and
the
findings
are
expected
to
be
generalized.
Sample
Representa?ve
subset
of
the
popula?on
the
researcher
studies
when
the
whole
popula?on
is
not
available
Sampling
Scheme
Specific
strategies
to
select
samples
Sampling
Design
Umbrella
term
that
includes
both
selec?ng
strategies
and
sample
size

3. Relationships
to
Remember
Research
Problem
• What
needs
to
be
studied
under
a
specific
situa?on
Research
Ques?on
• What
to
answer
or
test
Methodology
• How
to
gather
and
analyze
valid
data

4.
Sampling
Design
Research
Design
Data
Analysis
Methods
Valid
Informa.on
to
Answer
or
Test
Research
Ques.on

5. The
next
slides
will
present
a
basic
summary
of
some
of
the
sampling
schemes
that
are
widely
used
in
research.
However,
it
is
necessary
to
say
that
the
applica?on
of
probabilis?c
(random)
schemes
to
quan?ta?ve
research
and
non-­‐probabilis?c
(non-­‐random)
ones
to
qualita?ve
studies
does
not
imply
that
these
are
the
only
approaches.

6. In
fact,
Onwuegbuzie
&
Collins
(2007)
state
that
some
form
of
non-­‐random
scheme
is
the
most
common
choice
used
in
both
quan?ta?ve
and
qualita?ve
studies
and
that
random
ones
for
quan?ta?ve
research
and
non-­‐random
for
qualita?ve
studies
is
the
second
most
common
combina?on.
Our
own
research
into
disserta?on
and
thesis
work
interna?onally
demonstrates
that
the
majority
employ
purposeful
convenience
samples.
Such
predominance
of
non-­‐random
samples
is
related
to
the
fact
that
most
studies
in
social
sciences
cannot
be
done
under
experimental
condi?ons
in
which
pure
random
selec?on
is
expected.
Onwuegbuzie,
A.
&
Collins,
K.
(2007).
A
typology
of
mixed
methods
sampling
designs
in
social
science
research.
The
Qualita+ve
Report,
12
(2),
281-­‐316

7. Quantitative
Research
Simple
random
The
whole
popula?on
is
available
and
any
unit
has
the
same
chance
of
being
chosen
Stra.fied
random
The
whole
popula?on
is
divided
into
subpopula?ons
(strata)
with
respect
to
one
or
more
characteris?cs
that
interest
and
units
are
selected
from
each
stratum
at
random.
Alloca?on
of
units
can
be
done
equal
or
propor?onal
to
the
popula?on
Systema.c
Popula?on
is
ordered
according
to
a
criterion
and
units
are
chosen
from
the
list
by
selec?ng
every
nth
one
Cluster
Popula?on
consists
of
limited
groups
(clusters)
and
sampling
is
focused
on
selec?ng
clusters
instead
of
individual
units.
Not
all
clusters
are
included
in
the
sample
Mul.stage
random
Very
large
popula?ons
are
divided
into
clusters
and
then
sub-­‐clusters
and
units
are
selected
at
random
following
a
general
to
specific
direc?on

8. Qualitative
Research
(I)
Convenience
Sample
consists
of
units
that
are
available
and/
or
willing
to
par?cipate
Purposeful
Researcher
is
interested
in
studying
specific
groups.
Selec?on
of
units
can
be
done
at
random,
stra?fied,
or
using
more
than
one
scheme
(mixed)
Quota
Units
are
selected
in
rela?on
to
pre-­‐defined
characteris?cs
either
in
propor?on
to
popula?on
sub-­‐groups
or
minimum
number
from
each
sub-­‐
group
Snowball
Similar
units
are
required
and
access
to
them
is
done
by
asking
par?cipants
to
recommend
peers
Mul.stage
purposeful
Units
are
selected
in
more
than
one
stage
and
always
applying
a
purposive
scheme

9. Qualitative
Research
(II)
Typical
case
Units
are
chosen
because
they
represent
the
average
element
of
what
is
studied
Maximum
varia.on
When
differences
are
the
research
target,
dissimilar
units
are
chosen
to
form
sample
Criterion
Units
are
selected
because
each
one
of
them
represents
one
or
more
desired
criteria
Theore.cal
Units
are
chosen
because
they
can
provide
input
informa?on
to
build
or
test
a
theory

10. Mixed
Methods
Research
All
previous
schemes
When
choosing
samples
for
mixed
methods
studies,
researchers
need
to
take
into
account
the
purpose
of
the
study,
the
research
ques?ons,
and
the
stages
in
which
the
study
will
be
developed.
All
those
elements
help
them
select
the
most
appropriate
sampling
scheme
for
each
stage.
When
generaliza?on
is
the
main
concern
of
a
stage,
the
first
five
schemes
presented
are
the
best
op?ons.
When
understanding
is
the
focus
of
a
stage,
then
the
rest
of
schemes
should
be
considered.

11. Cases
to
Practice
Sampling

12. Quantitative
Research
• The research director
of an educational city
system that includes
forty-five elementary
schools wants to answer
the following research
question: What’s the
achievement in
mathematics of fifthgrade students of the
school system,
measured by a
standardized
achievement test?
Options for Sampling:
1. Simple random
2. Stratified random
3. Cluster
And the answer is…….

13. Cluster
Sampling
It’s
too
expensive
to
administer
the
test
to
the
whole
popula?on
and
the
same
happens
if
the
simple
random
sampling
is
chosen.
Stra?fied
random
sampling
implies
administering
the
test
to
some
of
the
students
of
a
class
and
not
to
others
and
that
may
be
inconvenient
from
the
students’
point
of
view.
Since
students
are
organized
in
classes
–which
are
in
fact
clusters,
the
most
appropriate
op?on
is
cluster
sampling
and
that
will
allow
to
test
all
students
in
the
chosen
classes.

14. Qualitative
Research
• A researcher wants to
know the reasons why
some employees of large
companies have strong
pro-mentoring duties
views.
Options for Sampling:
1. Purposeful
2. Snowball
3. Maximum variation
And the answer is…….

15. Snowball
Since
par?cipants
with
similar
views
within
organiza?ons
are
required
and
they
could
be
difficult
to
locate,
it
is
appropriate
to
ask
them
to
recommend
poten?al
subjects.

16. Sample
Size

17. Criteria
to
Select
Sample
Size
(I)
• Costs
(money,
?me,
and
effort)
to
get
sample
data.
• For
quan?ta?ve
studies:
– Popula?on
size
(the
larger
the
popula?on,
the
larger
the
sample)
– Confidence
interval
(how
much
error
will
be
allowed)
– Confidence
level
(how
much
confident
you
want
to
be
that
your
results
are
within
the
selected
confidence
interval)
– Standard
devia?on
(how
much
dispersion
from
the
mean
you
expect)
These
criteria
is
used
by
calculators
to
determine
the
most
appropriate
sample
size
for
your
study

18. Criteria
to
Select
Sample
Size
(II)
• For
qualita?ve
studies:
Samples
are
usually
small,
but
the
precise
number
is
very
unlikely
to
be
determined
at
the
beginning
of
the
study
.
The
main
criterion
is
to
have
a
sample
as
big
as
needed
to
have
all
the
informa?on
that
might
be
important.
Therefore,
when
informa?on
becomes
redundant,
the
sample
size
has
been
reached.

19. Criteria
to
Select
Sample
Size
(III)
• For
mixed
studies:
– Usually
the
sizes
of
the
sample
for
each
stage
are
different
– The
mixed
methods
variant
used
influences
the
sample
sizes.
For
example,
in
an
explanatory
design
the
same
par?cipants
must
be
included
in
all
the
stages
while
in
an
exploratory
design
more
par?cipants
are
needed
in
the
quan?ta?ve
stage.

20. Now
You
Know
1. The relationship between
research problem,
research question, and
sampling.
2. Some of the basic
sampling schemes you
may use to select
participants for your
study
Any
question?

21. Thanks
for
Coming
Hope you find this conference useful and
want to meet us soon