Sharon Seidman, Ph.D.
CAS 301
Review for Exam 1
CAS 301
Week 5
Sharon Seidman
CAS 301 Learning Objectives
Popular
Scholarly Writing
Writing
Writing about
Children
Audience
Everyone
Academic &
Professional
Access
Everywhere
Associations &
Universities
Review
For interest
For accuracy &
innovation
Evidence
Personal
sources
Text citations
Empirical data
Examples
Parenting
People
Child Development
Young Children
Review for Exam 1
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Sharon Seidman, Ph.D.
CAS 301
APA-Style Papers
Research Report
Title Page
Abstract
Introduction
Method
Results
Discussion
References
Graphs & Figures
Appendices
Literature Review
Title Page
Abstract
Introduction
Evidence
Literature
Experience
References
Graphs & Figures
Appendices
Abstract
Summary of entire paper
Included in library databases
Introduction
Topic Information
What paper is about
Why we should care
Background Information
Past research
Prior knowledge
Hypotheses/Expectations
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Sharon Seidman, Ph.D.
CAS 301
Method
What was done to
collect information?
Design
Participants/Sample
Materials
Procedure
Results
What was learned?
Description
Statistical analysis
No interpretation of
data
Discussion
What do results mean?
Comparison to expectations
Comparison to past research
Limitations
Interpretation
Review for Exam 1
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Sharon Seidman, Ph.D.
CAS 301
Expectations
Begins with hypothesis (general concept)
or question
Create specific, testable prediction
Prediction can specify relation or group
differences
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Sharon Seidman, Ph.D.
CAS 301
Variables
Basis for research
Individual elements of
hypotheses/predictions
Must vary
Has levels
A variable
Is a category Is a member of a
category
Can change
Cannot change
Different Types of Variables
pon
Res
t
jec
b
Su
at
Situ
se
ion
Variable Definitions
Concept
Valid
•Face
•Predictive
•Concurrent
•Convergent
•Discriminant
Review for Exam 1
Operation
Reliable
•Internal
•Test-retest
•Inter-rater
Scale
•Ratio
•Interval
•Ordinal
•Nominal
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Sharon Seidman, Ph.D.
CAS 301
Measurement Error
Goal = assess concept
Error = assess something else
Source of error:
Operational definition
doesn’t match
validity
Operational definition
isn’t consistent
reliability
Operational Quality - Validity
Construct validity
Measure assess concept
Measure doesn’t assess anything else
Internal validity
Study measures cause
No other explanation is
suggested
External validity
Study applies to real world
Results apply to population
of interest
Construct Validity
Face validity (subjective)
Criterion validity (objective)
Predictive (in future)
Concurrent
(between groups)
Convergent
(between measures)
Discriminant
(between measures)
Review for Exam 1
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Sharon Seidman, Ph.D.
CAS 301
Operational Quality - Reliability
Test-retest
Alternate forms
Internal consistency
Split-half
Cronbach’s alpha (α)
Ranges from 0 to 1
.60 is acceptable
.80 is good
Inter-rater
Review for Exam 1
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Sharon Seidman, Ph.D.
CAS 301
Frequency Distributions
Three styles
Pie graphs
Bar graphs
histograms
Line graphs
frequency polygons
Select based on
Type of scale
Number of variables
Point to be emphasized
Review for Exam 1
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Sharon Seidman, Ph.D.
CAS 301
Receptive Language
Girls
Boys
Emerging
Emerging
6%
Not Yet
13%
Not Yet
7%
16%
Fully
Fully
50%
53%
Almost
Almost
28%
27%
Receptive Language
60%
50%
40%
Girls
Boys
30%
20%
10%
0%
Not Yet
Emerging
Almost
Fully
Receptive Language
Girls
60%
Boys
50%
40%
30%
20%
10%
0%
Not Yet
Review for Exam 1
Emerging
Almost
Fully
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Sharon Seidman, Ph.D.
CAS 301
Describing Groups
Central Tendencies
Mean: mathematical average
Median: middle score
Mode: most common score
Variability
Range:
smallest to largest score
Standard Deviation:
normality of central tendency
Normal
Skewed
Goals of Research
Description
Prediction
Causation
Review for Exam 1
Descriptive
Statistics
Inferential
Statistics
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Sharon Seidman, Ph.D.
CAS 301
Two Variable Graph
Mean Score for Group Members
Two Variable Graph
Individual Score for Each Person
106
PPVT-R
104
102
100
98
96
94
92
90
88
86
4
5
6
7
Age
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Sharon Seidman, Ph.D.
CAS 301
Linear Relation
Nature of Linear Relation
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Sharon Seidman, Ph.D.
CAS 301
Curvilinear Relation
Correlation Coefficient
-1.00 to -.70 =
- .69 to -.30 =
- .29 to -.00 =
.00 to .29 =
.30 to .69 =
.70 to 1.00 =
Strong Negative
Moderate Negative
Weak Negative
Weak Positive
Moderate Positive
Strong Positive
Factors Influencing Correlation
Restriction of range
Multiple correlations
Partial correlations
Review for Exam 1
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Sharon Seidman, Ph.D.
CAS 301
Limitations & Requirements
Limitations
Linear relation only
Association isn’t cause
Sample influences strength
Requirements
Mathematical data
Ratio, Interval, Likert
Adequate sample size
Utility
Description
Prediction
Structural modeling
Review for Exam 1
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Sharon Seidman, Ph.D.
Review for Exam 1
CAS 301
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