Norming 28Sept12 p1 - Flash (Large) - 20120928 01.46.55PM
X
Today
Slide 3
Onto Norms
Good old memories
Standard Normal Distribution
Good old memories
Standard Normal Distribution
Slide 7
Slide 8
Slide 13
Slide 8
Slide 14
Slide 8
Slide 9
Slide 10
Slide 9
Slide 10
Slide 14
Slide 10
Slide 14
Slide 10
Slide 11
Slide 13
Slide 11
Slide 12
Slide 13
Slide 14
Arbitrary Metrics: Some definitions Blanton, & Jaccard, J., (2006). Arbitrary metrics in psychology. American Psychologist (61), 27-41.
Slide 14
Slide 13
Slide 12
Slide 13
Slide 12
00:00
/
00:00
CC
9/28/2012
Today
Syllabus/Course
Review
A
short
survey
Norming
Overview
Quickie
review
of
the
fundamentals
Arbitrary
Metrics
What’s
the
big
deal?
Normative
Comparisons
The
issue
Examples
How-to
j0196060
9/28/2012
Where
are
YOU
on
the
graph?
What
was
the
best
score
to
have?
9/28/2012
Onto
Norms
You
take
the
midterm.
You
get
a
score
of
48.
What’s
the
MOST
important
thing
to
know
about
that
score?
MCj00890380000[1]
Norms
are
empirically
established
by
determining
what
persons
in
a
representative
group
actually
do
on
the
test.
9/28/2012
Good
old
memories
9/28/2012
Standard
Normal
Distribution
M
=
40;
SD
=
4.94
What
would
a
raw
score
be
if
it
fell
at
1SD
above
the
mean?
And
it
is
at
or
above
what
percent
of
the
cases?
40
+
4.9
=
44.9;
at
or
above
84.13%
of
cases
Fun!
9/28/2012
Good
old
memories
9/28/2012
Standard
Normal
Distribution
M
=
40;
SD
=
4.94
What
would
a
raw
score
be
if
it
fell
at
1SD
above
the
mean?
And
it
is
at
or
above
what
percent
of
the
cases?
40
+
4.9
=
44.9;
at
or
above
84.13%
of
cases
Fun!
9/28/2012
Where
does
a
score
of
35.06
fall?
1
SD
below
the
mean;
at
or
above
15.87%
of
the
cases.
What
is
the
score
and
percentile
of
a
score
that
is
2
SDs
above
the
mean?
49.88;
97.72
percentile.
M
=
40;
SD
=
4.94
More
Fun!
9/28/2012
What
is
the
percentile
rank
of
a
raw
score
of
34?
M
=
40;
SD
=
4.94
Using
the
negative
half
of
the
table
for
the
Area
under
the
Standard
Normal
Curve
for
Values
of
z,
we
find
.1131
as
the
cumulative
probability
value.
PR34
=
11%.
If
you
get
a
raw
score
of
34,
you
score
better
or
equal
to
11%
of
the
sample.
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
11%
11%
9/28/2012
Link
to
last
slide
viewed
9/28/2012
What
is
the
percentile
rank
of
a
raw
score
of
34?
M
=
40;
SD
=
4.94
Using
the
negative
half
of
the
table
for
the
Area
under
the
Standard
Normal
Curve
for
Values
of
z,
we
find
.1131
as
the
cumulative
probability
value.
PR34
=
11%.
If
you
get
a
raw
score
of
34,
you
score
better
or
equal
to
11%
of
the
sample.
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
11%
11%
9/28/2012
Link
to
last
slide
viewed
9/28/2012
What
is
the
percentile
rank
of
a
raw
score
of
34?
M
=
40;
SD
=
4.94
Using
the
negative
half
of
the
table
for
the
Area
under
the
Standard
Normal
Curve
for
Values
of
z,
we
find
.1131
as
the
cumulative
probability
value.
PR34
=
11%.
If
you
get
a
raw
score
of
34,
you
score
better
or
equal
to
11%
of
the
sample.
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
11%
11%
9/28/2012
What
is
the
percentile
rank
for
a
raw
score
of
47?
M
=
40;
SD
=
4.94
The
cumulative
area
for
z
=
1.42
is
.9222
PR47
=
92%
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
9/28/2012
What
raw
score
would
we
expect
to
find
at
the
75th
percentile?
M
=
40;
SD
=
4.94
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
Hint,
z
=
.68
corresponds
to
a
cumulative
area
(aka
probability)
of
.75.
9/28/2012
What
is
the
percentile
rank
for
a
raw
score
of
47?
M
=
40;
SD
=
4.94
The
cumulative
area
for
z
=
1.42
is
.9222
PR47
=
92%
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
9/28/2012
What
raw
score
would
we
expect
to
find
at
the
75th
percentile?
M
=
40;
SD
=
4.94
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
Hint,
z
=
.68
corresponds
to
a
cumulative
area
(aka
probability)
of
.75.
9/28/2012
Link
to
last
slide
viewed
9/28/2012
What
raw
score
would
we
expect
to
find
at
the
75th
percentile?
M
=
40;
SD
=
4.94
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
Hint,
z
=
.68
corresponds
to
a
cumulative
area
(aka
probability)
of
.75.
9/28/2012
Link
to
last
slide
viewed
9/28/2012
What
raw
score
would
we
expect
to
find
at
the
75th
percentile?
M
=
40;
SD
=
4.94
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
Hint,
z
=
.68
corresponds
to
a
cumulative
area
(aka
probability)
of
.75.
9/28/2012
What
raw
score
would
we
expect
to
find
at
the
20th
percentile?
M
=
40;
SD
=
4.94
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
Hint:
What
is
the
z
score
for
a
cumulative
area
(aka
probability
of
.20)?
9/28/2012
Link
to
last
slide
viewed
9/28/2012
What
raw
score
would
we
expect
to
find
at
the
20th
percentile?
M
=
40;
SD
=
4.94
Link
to
negative
z-values
table.
Link
to
positive
z-values
table.
Hint:
What
is
the
z
score
for
a
cumulative
area
(aka
probability
of
.20)?
9/28/2012
The
z-score
or
standard
score
is
what
type
of
transformation?
Linear
9/28/2012
Link
to
last
slide
viewed
9/28/2012
Link
to
last
slide
viewed
9/28/2012
15
Arbitrary
Metrics:
Some
definitions
Blanton,
&
Jaccard,
J.,
(2006).
Arbitrary
metrics
in
psychology.
American
Psychologist
(61),
27-41.
Metric:
the
numbers
that
the
observed
measures
take
on
when
describing
individuals’
standing
on
the
construct
of
interest
e.g.,
self-esteem
metric
might
range
from
1
(lowest
possible)
to
7
(highest
possible)
Arbitrary
Metric:
A
metric
is
arbitrary
when
it
is
not
known
where
a
given
score
locates
an
individual
on
the
underlying
psychological
dimension,
or
how
one-unit
change
on
the
observed
score
reflects
the
magnitude
of
change
on
the
underlying
dimension.
Until
psychologists
know
what
psychological
reality
surrounds
the
different
scores
on
a
scale;
the
response
metric
is
arbitrary.
9/28/2012
Link
to
last
slide
viewed
9/28/2012
Link
to
last
slide
viewed
9/28/2012
The
z-score
or
standard
score
is
what
type
of
transformation?
Linear
9/28/2012
Link
to
last
slide
viewed
9/28/2012
The
z-score
or
standard
score
is
what
type
of
transformation?
Linear