Lecture5-Jan+19th-Measuring+variables

Lecture5-Jan+19th-Measuring+variables -  

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview:   Tutorial/quiz
3
due
TODAY
   Thursday
=
Tutorial/Quiz
4
   Grades
for
Quiz
2
are
not
showing
up!
   Exercise
2
will
be
posted
today
after
class.
   New
due
date
is
TUESDAY
Jan
26th
   NEXT
WEEK
   EXAM
1
coming
up!!!!!!
   Review
session
times
will
be
communicated
 next
lecture
   ONLINE
Review
session
   WHAT
TO
EXPECT
ON
EXAM?
   50
MC
questions
(5
pts
each)
   HOW
DO
I
DO
WELL
ON
TEST?
   Come
to
class
   Review
lecture
notes
   Go
over
book
descriptions
of
concepts
covered
in
 class
   Generating
Hypothesis
   Characteristics
of
Hypotheses
   Defining
variables
   Setting
up
a
study
   Research
hypothesis
=
Testable
 prediction
   Specific
   Falsifiable
   Characteristics
of
hypotheses:
   Descriptive
vs.
Causal
   Directional
vs.
Non‐directional
   Choice
of
directional
vs.
non‐directional
depends
on
 previous
research,
theory
etc.
   Variable:
two
or
more
levels
of
a
 characteristic,
event,
trait,
etc…
   Operational
definition
   Definition
of
procedure
used
by
research
to
 measure
or
manipulate
variable
   Operational
definition
   Definition
of
procedure
used
by
research
to
 measure
or
manipulate
variable
   Some
variables
are
easier
to
quantify
that
others
 ▪  Memory
vs.
Extraversion
   As
long
as
something
is
numerically
qualified,
it
can
 be
measured!
 ▪  Different
ways
of
doing
it…we’ll
discuss
it
later…
   Descriptive
(Describe)
   Correlational
(Predict)
   Experimental
(Explain)
   What
is
the
main
different
among
the
three?
   Level
of
control
exerted
by
researcher

   Why
only
experimental
method
allows
for
 cause
and
effect
conclusions?
   Direct
manipulation
of
variables!!!
 Independent
vs
Dependent
Variables
   Independent
Variable
(IV)
=
Manipulated
or
 Causal
Variable
   Dependent
Variable
(DV)
=
affected
or
 outcome
variable
     True
IV=manipulated

experiment
   Not
true
IV=not
manipulated

quasi‐ experiment
   participant
variable
(e.g.,
gender,
age,
 etc.)
   Study
descriptions
will
be
provided.
   You’ll
need
to
identify:
   IVs
and
their
level
(true
IV
or
not?)
   DVs
   Operational
definitions
   Generating
Hypothesis
   Descriptive
vs.
causal
   Directional
vs.
non‐directional
   Identifying
and
defining
variables
   Setting
up
a
study
   Choosing
study
type
   Choosing
measures
   Choosing
participants
   Depends
on
the
characteristics
of
our
 hypothesis!
   Descriptive:
Formal
statement
of
a
predicted
 observation
 ▪  Correlational
   Causal:
Explains
possible
cause
for
the
 pattern
stated
in
the
descriptive
hypothesis. 
 ▪  Experimental
 Allow
us
to
study:
   Are
two
things
related
to
each
other?
   What
is
the
direction
of
the
association?
   What
is
the
strength
of
the
association?
   Relationship
is
measured
by
a
correlation
 coefficient
   Descriptive
Hypotheses
   Non‐directional
 ▪  There
is
a
relationship
between
age
and
amount
of
veggie
 eaten
in
a
week
   Directional
 ▪  As
children
grow,
they
eat
more
veggies
   Existence
 Age
   Direction
 Age
 Amount
of
veggies
 Age
 Amount
of
veggies
 Amount
of
veggies
   Strength
 Strong
 Correlation
 moderate
 Correlation
   Correlation
coefficient

   Is
represented
by
r
   Ranges
from
–1
to
1
   Allow
us
to
answer:
   Are
two
things
related
to
each
other?
   What
is
the
direction
of
the
association?
   What
is
the
strength
of
the
association?
   Are
two
things
related
to
each
other?
   If

r
=
0
:
no
   If

r
≠
0
:
yes
   What
is
the
direction
of
the
association?
   If
–1
<
r
<
0
:
negative
correlation
   If

1
>
r
>
0
:
positive
correlation
   What
is
the
strength
of
the
association?
   As
r
gets
close
to
zero
the
correlation
gets
weaker
   As
r
gets
close
to

1

the
correlation
gets
stronger
 •  Direction
of
causation
is
unknown
 •  Possible
third
variable
   Spurious
correlation
   Depends
on
the
characteristics
of
our
 hypothesis!
   Descriptive
 ▪  Correlational
   Causal:
Explains
possible
cause
for
the
 pattern
stated
in
the
descriptive
 hypothesis. 
 ▪  Experimental
   Hypothesis
   Children
who
know
that
veggies
are
healthy
will
 choose
them
to
a
greater
extent
compared
to
 children
without
that
knowledge
 ▪  Directional
hypothesis
   Experiment
   Manipulation











Effect
   Experiment
   Manipulation











Effect
 Knowledge
 Type
of
video
watched:
 informative
vs.
not
 Choice
 Choosing
broccoli
over
 crackers
 Independent

 variable
 Type
of
video
watched:
 info
or
no
info
 Experimental
 group
 Control
 group
   How
are
we
sure
that
any
potential
effect
is
 due
to
our
IV?
   We
need
to
ensure
that
the
only
difference
b/w
 the
“experimental”
and
“control”
group
is
 exposure
to
our
manipulation!
   Random
assignment
   Ensures
each
participant
has
SAME
probability
to
 be
in
either
group
   Ensures
that
any
difference
is
averaged
out!
   Choosing
study
type
   Type
of
study
depends
on
type
of
hypothesis
we
 are
interested
in
testing
 ▪  Descriptive
=
Correlational
study
 ▪  Causal
=
Experimental
study
   Generating
Hypothesis
   Descriptive
vs.
causal
   Directional
vs.
non‐directional
   Identifying
and
defining
variables
   Setting
up
a
study
   Choosing
study
type
   Choosing
measures
   Choosing
participants
   How
do
we
measure
variables?
   Measurement
Types
   Measurement
scales
   Decide
of
the
measurement
type
   Behavioral
   Physiological
   Self‐report
   Test
   How
do
we
measure
variables?
   Measurement
Types
   Measurement
scales
   Nominal
Scale
   Numbers
represent
groups
   Label
categories
 Examples
   Performance
on
exam
 ▪  Pass=1
 ▪  Fail=0
   Gender
 ▪  Females=999
 ▪  Males=777
   Ethnicity
 ▪  ▪  ▪  ▪  Caucasian=1
 African‐American=2
 Asian‐American=3
 Other=4
   Ordinal
Scale
   Meaningfully
ordered
   Know
which
is
greater
   Do
not
know
how
much
 greater
 Examples
   Self‐Esteem
 ▪  Low=1
 ▪  Med=2
 ▪  High=3
   Reading
group
 ▪  Low
 ▪  Med
 ▪  High
   Ranking
participants
 from
worst
to
best
   Interval
Scale
   Numeric
values
represent
equal
distance
   No
true
zero
point=>
values
can
be
negative
   Ratio
Scale
   Absolute
zero
   Relative
magnitude
 3’ 4’ 7’ 12’ 1=“short” Nominal 14’ 24’ 2=“tall” Ordinal 1 2 3 4 5 6 Interval 0 1 4 9 11 21 Ratio 3 4 7 12 14 24   Depends
on
your
question
   Do
two
group
differ?
 Nominal   Does
one
group
have
more?
 Ordinal   How
much
more?
 Interval   Three
times
as
much?
 Ratio   Depends
on
your
planned
statistical
analyses
   Nominal
and
ordinal
data
=>
nonparametric
 statistical
tests

   Interval
and
ratio
data
=>
parametric
statistical
 tests 

   Likert
Scales
   Are
actually
NOMINAL
scales
   In
practice
used
as
interval
scales
 Strongly Moderately Slightly Neutral Slightly disagree disagree disagree agree 1 2 3 4 5 Moderately Strongly agree agree 6 7   Climate
 IV
   Ego‐oriented
   Task
oriented
 IV
levels
   Persistence
in
task
completion
 DV
   Number
of
attempts
at
completing
tasks
 Behavioral
 measure/
 Ratio
scale
 Operational
 definition
of
 DV
 ...
View Full Document

This note was uploaded on 06/21/2011 for the course PSYCHOLOGY Psych 41 taught by Professor Castelli during the Winter '10 term at UC Davis.

Ask a homework question - tutors are online