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Introduction to Experimental
Research
Lawrence R. Gordon
Psychology Research Methods I
From last class…Descriptive
Stats
 DISPLAYING DATA -- distributions,
graphs,…”pictures”
 Properties of distributions – symmetry, modality,
skewness
 Continuing today…
 SUMMARIZING DATA – measures of central
tendency & variability, …”numbers”
Descriptive Statistics
 Name some you know of...
 What can they do for us?
– Tell us more about our data -- Location
– Tell us more about our data -- Spread
– Help us communicate these to others!
• Highly summarized
• Basis of results and tables in reports of studies
Measures of Central Tendency
 Mode
– the “typical” score
– the peak(s) of the frequency distribution
 Median
– the “center” score
– splits distribution into two halves (by area)
 Mean
– the (arithmetic) “average” of the scores
– the balance point of the distribution
(“seesaw”)
Central Tendency, contd.
 Pros and Cons -– Mode
– Median
– Mean
 Relationships to distribution shapes -– Symmetric: Mode = Median = Mean
– Skewed:
Pos (rgt)- Mo < Md < Mn
Neg (lft)- Mn < Md < Mo
Variability
 Range
– Hi - Lo score
– “Goes with” Mode
 Interquartile range (IQR)
– 75th-%ile - 25th-%ile scores
– “Goes with” Median (50th-%ile score)
 Standard Deviation (SD)
– Sqrt of average of sqrd deviations around Mn
– “Goes with” Mean [Handout for reference]
Real Data
 First Hour Exam Scores
FIRST HOUR EXAM: Psyc 109, Fall 02
FIRST EXAM GRADE (of 50)
Exam I, 9/26/02
Valid
Missing
Mean
Median
Mode
Std. Deviation
Variance
Range
Minimum
Maximum
Percentiles 25
50
75
234
1
37.9829
38.0000
37.00
4.51128
20.35164
24.00
24.00
48.00
35.0000
38.0000
41.0000
Frequency
N
Psyc 109 9/26/02
70
60
50
40
30
20
Std. Dev = 4.52
10
Mean = 38.0
N = 233.00
0
25.0 27.5 30.0 32.5 35.0 37.5 40.0 42.5 45.0 47.5
Number Correct out of 50
Real Data
 Baseball salaries revisited
BASEBALL SALARIES 1994
A
BASEBALL SALARIES 1994
L
S
N
V
7
M
0
M
8
M
0
200
M
0
S
3
V
2
S
7
100
S
9
Frequency
300
Std. Dev = 1390922
0.0
00 0
00
60 000.
0
00
55 000.
0
00
50 000.
0
00
45 000.
0
00
40 000.
0
00
35 000.
0
00
30 000.
0
00
25 000.
0
00
20 000.
0
00
15 000.
00
10 00.0
00
50
0.0
R
0
Mean = 1183416.7
M
0
N = 747.00
0
M
0
P
2
0
5
0
7
0
SALARY94
Real Data
 109 Questionnaire - Scales (briefly!)
COURSE QUESTIONNAIRE CFC SCALE
“Concern for Future Consequences” Scale
Descriptive Statistics
t
CFC Scale (Range 12 - 60)
60
8
50
Frequency
9
0
40
0
6
30
8
3
20
7
0
10
0
0
0
0
15.0
0
0
i
Statistics
s
CFCN
Scale (Range 12 - 60)
V
N N
Valid
7
174
M
Missing
9
22
M
Mean
0
40.9339
M
Median
0
41.0000
M
Mode
0
40.00
Std.S
Deviation
0
7.2553
V
Variance
4
52.6387
S
Skewness
7
-.325
Std.S
Error of Skewness
8
.184
R
Range
0
43.00
Std. Dev = 7.26
M
Minimum
0
17.00
Mean = 40.9
M
Maximum
0
60.00
N = 174.00
P
2
Percentiles
25
0
37.0000
20.0 25.0 30.0 35.0 40.0 45.0 50.0 55.0 60.0
5
50
0
41.0000
7
75
0
46.0000
CFC Scale (Range 12 - 60)
COURSE QUESTIONNAIRE: NC SCALE
“Need for Cognition” Scale
Descriptive Statistics
t
NC Scale (Range 18 - 90)
i
s
N
N
V
8
7
M
9
M
9 30
0
M
0
0
M
0
0
S
6 20
0
V
8
4
S
3
7
S
7
8
10
R
0
0
Std. Dev = 11.65
M
0
0
Mean = 62.6
M
0 0
0
N = 187.00
P
2
0
25.0 0
35.0 45.0 55.0 65.0 75.0 85.0
30.00
40.0 50.0 60.0 70.0 80.0 90.0
5
0
7
0
0
NC Scale Scores
Frequency
40
Real Data
 My dissertation data
 A NOTE TO END ON: not everything
interesting in data is captured by a single
statistic! We must get to know data well,
from many angles, to find its message!
 NOW…on to our current topic,
Experimental Research...
NOW, RESUMING…
 Intro to Experimental Research,
 A “pseudo-example”…
 “Time flies when you’re having fun”!
– DOES IT?
A Simple Experiment: “Time Flies”
 EXAMPLE: “Time flies when you’re
having fun”
 Hypothesis: IF one is “having more fun”, THEN time
will seem to pass more quickly
 Design:
• IV: 100 persons randomly assigned to two groups:
– 1: “Having more fun”
– 2: “Having less fun”
• DV: Estimate of a standard 10 minute interval
 Procedure: manipulation of cartoon captions
A Simple Experiment, cont.
 EXAMPLE: “Time flies when you’re
having fun” (cont..)
 Results
– “Raw data”
– Organized by “frequency distribution”
– Graphs of data
• Group “dotplots”
• Group histograms
 Quickie summary of results: “More fun” group gave
shorter estimates on average than “Less fun” group.
A Simple Experiment, cont.
 RESULTS
– How describe?
• List of scores
• A picture
• A single number or two?
– LOCATION = “central tendency”
– SPREAD = “variability”
“Having Fun” Data
1
1
2
2
2
2
1
1
1
1
2
2
1
2
2
2
2
2
2
1
2
1
1
1
2
2
2
6.1
10.9
13.7
13.8
9.2
14.3
15.3
9.1
8.5
10.4
8.1
8
10.5
9.7
15.7
16.5
15.5
11.5
7.1
6.5
15
11.5
8
11.2
9.3
12.2
13.6
2
1
1
2
1
2
1
1
1
2
2
1
2
2
2
1
2
2
1
2
2
1
1
2
2
1
1
12.5
10.4
7.1
14.4
11.4
13.4
6.3
7.5
9.5
17.7
10.9
7.5
6.9
11.2
21.8
6.4
13.9
11
5.8
13.2
13
10.1
5.4
13
4.9
10.2
8.6
1
2
1
1
2
2
2
2
1
1
1
1
2
2
2
2
2
2
1
2
1
1
1
2
2
1
1
11.9
13.2
8.4
8.8
10.3
12.4
12.1
8.7
11.5
6.1
10.2
4.1
13.6
13.2
14.2
16.1
18.2
15.5
10.2
11.2
7
6.2
6.7
14.3
12.8
11.3
7.8
2
1
2
1
1
2
1
1
1
1
1
1
1
2
1
1
2
2
1
17.1
11.4
5.3
8.5
10
10.3
7.7
0.4
9.2
11.4
8.9
3.1
12.3
10.4
5.8
5.3
15.3
9
11.8
“HAVING FUN” DESCRIPTIVE STATISTICS:
HISTOGRAMS W/ LEGENDS
COND:
1 'More fun' (Captions)
COND:
10
10
8
8
6
6
4
4
2
2
Std. Dev = 2.72
Mean = 8.6
N = 50.00
0
Std. Dev = 3.35
Mean = 12.5
N = 50.00
0
.0
22.0
21.0
20.0
19.0
18.0
17.0
16.0
15.0
14.0
13.0
12.0
11.0
10
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
.0
22.0
21.0
20.0
19.0
18.0
17.0
16.0
15.0
14.0
13.0
12.0
11.0
10
9.0
8.0
7.0
6.0
5.0
4.0
3.0
2.0
1.0
0.0
Estimate of 10 minute interval
2 'Less fun' (No Captions)
Estimate of 10 minute interval
“HAVING FUN” DESCRIPTIVE
STATISTICS: TABLES
'More fun' (Captions)
t
5
8
0
.
5
4
1
3
.
.
.
0
0
2
'Less fun' (No Captions)
i
a
s
E
N
V
0
M
0
M
4
M
0
M
2
S
3
V
0
S
7
S
7
R
9
M
9
M
8
P
2
0
5
0
7
5
a
E
A Simple Experiment, cont.
 Results (cont.)
– Group 1 = “More fun”
• Mean = 8.60, SD = 2.72, N = 50
– Group 2 = “Less fun”
• Mean = 12.48, SD = 3.35, N = 50
– Quickie summary of results: the “More fun”
group gave shorter estimates of the 10-minute
interval, on average, than the “Less fun”
group.
NOTE on the Mean & the SD
 Most frequently used -- whenever possible
 Often called “location” and “scale” -- why?
 Examples of use with NORMAL curve (the
“bell” curve) --– Why used frequently?
– Various commonly used “standard” scales
 THAT’S ALL, FOLKS!