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What does a test score of 85 (out of 100) indicate?
When you get a test back in class, what is one of the first questions that you ask?
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0 10 20 30 40 50 60 70 80 90 100
Test Score Distribution
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Low Variability
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40 45 55 60 70 75 80 90 100
Test Scores
40 45 55 60 70 75 80 90 100
Test Scores
Positively Skewed
Distribution
Negatively Skewed
Distribution
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-4 -3 -2 -1 Mean +1 +2 +3 +4
Central Tendency
a) Mode (most frequent score)
b) Mean (average score; [EX/N])
c) Median (midpoint of scores)
Variability (Spread in Scores)
a) Range (lowest to highest score)
b) Standard Deviation
c) Variance
Normal Curve
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X
10
20
30
40
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-20
-10
0
10
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Computation of Standard Deviation & Variance
x
(EX/N) = 30 (Mean)
EX = 150
Test Scores
Deviation scores (scores
minus the mean
x2
400
100
0
100
400
Squared deviation scores
EX2 = 1000 (Sum of the squared deviation scores)
EX2/N = 200 (the variance or s2)
200 = 14.14 (standard deviation)s2 = standard deviation or s
Mean of the sum of the squared deviation scores
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-4 -3 -2 -1 Mean +1 +2 +3 +4 Test Score
13.59% 34.13% 34.13% 13.59%
0.13% 2.14%2.14% 0.13%
Number of Cases
Z score
T score
CEEB score
Deviation IQ (SD = 15)
Stanine
Percentile
-4 -3 -2 -1 0 +1 +2 +3 +4
10 20 30 40 50 60 70 80 90
200 300 400 500 600 700 800
55 70 85 100 115 130 145
4% 7% 12% 17% 20% 17% 12% 7% 4%
1 2 3 4 5 6 7 8 9
1 5 10 20 30 40 50 60 70 80 90 95 100
Relationships Among Different Types of Test Scores in a Normal Distribution
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Test Score – Mean
Standard DeviationZ SCORE =
~ Standard Score ~
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Fathers Height (in inches)
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Son’s Height
85
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Correlation --- Some Key Concepts
a) Consists of a set of ordered pairs
b) Indicates both the magnitude and direction of the relationship between variables
c) Range is from -1.0 to + 1.0
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Widely Reported Correlations
Smoking and lung cancer
Media violence and aggression
Condom use and sexually transmitted HIV
Passive smoking and lung cancer at work
Lead exposure and children’s IQNicotine patch and smoking cessation
Calcium intake and bone massHomework and academic achievementAsbestos and laryngeal cancerSelf-examination and breast cancer
-.2 -.1 0 .1 .2 .3 .4
From Bushman, B.J., & Anderson, C. A. (2001). Media violence and the American public: Scientific facts versus media misinformation, American Psychologist, June/July, 477-489.
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Test Scores
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Job
Perform
ance
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Positive Correlation
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Absenteeism (in hours)
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Job
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Negative Correlation
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Test Scores
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Job
Perform
ance
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Significant Correlation
Poor
Good
Fail Pass
Correct Acceptances
False Rejections
Correct Rejections
False Acceptances
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Test Scores
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Job
Perform
ance
85
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No Correlation
Poor
Good
Fail Pass
Correct Acceptances
False Rejections
Correct Rejections
False Acceptances
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Test Scores
Job Performance
Scores
100
50
0
100
50
0
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Test Scores
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Job
Perform
ance
85
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**
**
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Poor
Good
Fail Pass
Correct Acceptances
Correct Rejections
False Acceptances
Significant Correlation
False Rejections
Effect of raising cutoff score?
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Test Scores
60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85
Job
Perform
ance
85
84
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**
**
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Poor
Good
Fail Pass
Correct Acceptances
Correct Rejections
False Acceptances
Significant Correlation
False Rejections
Effect of lowering cutoff score?
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Observation
Statement of the Problem (Research Question)
Design Study
Measurement (Collect Data)
Basic Steps in Research
Statistical Analysis
Interpretation (Conclusion)
• State Hypotheses
• Use/Generate a Theory
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~ Tips for Choosing a Research Topic ~
• Read, read, read (e.g., journal articles) to generate research ideas
• Pick a topic that interests you (it will be more fun to do)
• Be realistic (pick a topic that can be accomplished in a reasonable time frame)
• Improve on prior research (e.g., “limitations of present study,” “suggestions for future research”)
• Minimize problems, time delays in data collection phase of research
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Basic Scales of Measurement
1) Nominal (Categorization or classification)
• Yes/No, True/False
• Male/Female
2) Ordinal (Ranking)
• 1st, 2nd, 3rd
1) Interval (Equal intervals exist between points on the scale)
_______ _______ _______ _______ _______
1 2 3 4 5
• Ratio (an absolute zero point exists)
2) Kelvin scale of temperature
3) Time
4) Height, Weight
Measurement: The assignment of numerals to events or objects according to certain rules
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• Limit collection of categorical data
Age
0 - 1819 – 2526 – 3536 – 4546 – 5556 – 6585 & Above
Income
0 ------ 10,00010,001 – 25,000 25,001 – 35,00035,001 – 50,00050,001 – 75,00075,001 – 100,000100,000 & Above
Age in Years: _______
Income: ____________
~ I-O Research ~Measurement
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~ I-O Research ~Measurement (cont.)
Yes _____
No __________ _____ _____ _____ _____
1 2 3 4 5 Highly HighlyDisagree Agree
• Limit collection of dichotomous data
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~ I-O Research ~Measurement (cont.)
• Restrict possibility of missing data
1.2.3.4.5.
4849 50
Scale Questions
Missing
Missing
Computed score for scale or subscales containing questions #5
and #48 will also be missing
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~ Key Terms ~
Independent variable (IV) (predictor): One that can be manipulated or used to predict scores on the dependent variable
Dependent variable (DV) (criterion): The variable of interest; the one you are attempting to understand or affect
• SAT, ACT scores used to predict success in college
• Interview scores used to predict performance in a job
IVs DVs
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Design Options
Control Realism
Laboratory Experiment
• Manipulate independent variable
• Precise measurement of dependent variable
Case study
• Detailed information
• Low generalizability
Naturalistic observation
Field study
Survey research
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~ I-O Research ~
Interesting fact: Substantial amount of I-O studies are non-experimental (about 50%)
Overall Point:
Best for research to be driven by theories and problem-solving approaches not by methodology/statistics
• Much research efforts in I-O focus on rather trivial questions that can be studied with “fancy” techniques
• Bulk of research has limited applied significance
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Some Pre-Experimental Designs
Static Group ComparisonX O
O
One-Shot Case Study
X O
X = Treatment or Intervention
O = Observation or Collection of Data
One-Group Pretest-Posttest Design
O X O
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Math
Pretest
55
64
44
33
28
63
48
38
46
47
Math
Posttest
56
66
46
38
29
63
50
40
48
47
English
Pretest
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35
43
36
20
60
40
31
52
64
English
Posttest
35
37
47
36
21
62
40
31
56
66
6-week training program between tests
Did the program work to increase scores?
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% increase
100
90
80
70
60
50
40
30
20
10
0
Math English
“Lying” with numbers
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An organization reports that accidents have decrease substantially since they began a drug testing program. In 1995, the year before drug testing, the number of accidents was 50. In 1996, the year testing began, the amount dropped to 40. In 1997, the year after drug testing the number of accident dropped to 29. What do you make of this?
1995 Drug Testing
55
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25
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15
10
5
1997
*
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*
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65
60
55
50
45
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35
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25
20
15
Given the illustration below, now what do you make of the effectiveness of the drug testing program?
1992 1993 1994 1995 1996 1997 1998 1999 2000
*
*
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*
**
*
*
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Multiple Time-Series DesignO1 O2 O3 O4 O5 X O6 O7 O8 O9 O10
O1 O2 O3 O4 O5 O6 O7 O8 O9 O10
Some Quasi-Experimental Designs
O1 O2 O3 O4 O5 X O6 O7 O8 O9 O10
Time-Series Design
O X O
O O
Non-Equivalent Control-Group Design
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R O X O
R O O
R indicates randomization
Pretest-Posttest Control Group Design
R X O
R O
Posttest-Only Control Group Design
Some True Experimental Designs
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~ Basic Ethics in Research ~
Informed Consent
Right to Privacy
Anonymous, confidential treatment of data
Protection from Deception (cost-benefit assessment)
Debriefing e.g., (explanation of the purpose of the study)
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50
45
40
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5
0
J F M A M J Jul Aug S O N D
At first glance, anything happening here?
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J F M A M J Jul Aug S O N D
How about now?
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