1. Week 2 Continued:
Variables
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2. Independent and Dependent Variables
 Independent variable
 Variables that are thought to influence
or explain variation in the dependent
variable.
 Experimental treatment or predictor
variables.
 Dependent variable
 Criterion or outcome variable.
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3. Examples of Independent Variables
 Teaching Method
 Diet Plan
 Medication
 Gender
 Age
 Treatment Condition
 Achievement Score
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4. Examples of Dependent Variables
 Attitudes
 Success in graduate school
 Homesickness of first year at college
 Success at controlling behavior
 Reduction of symptoms
 Achievement Score
 Time in 100 meter dash
*The independent and dependent variable depends
on the research question being asked.
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5. Variable Name vs. Variable Values
 Variable name - properties of objects,
events, and people that can take on
different values
 Hair color
 Gender
 Speed
 Goal orientation
 Self-esteem
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6. Variable Name vs. Variable Values
 Variable values: values of variable name
Variable Name Variable Value
Hair color Brown, blond, black, red
Gender/sex Male, female
Goal orientation Performance-approach,
Mastery-approach
Speed MPH
Self-esteem Score on survey computed,
low, medium, high
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7. Identifying IV and DV
 I want to determine if third grader’s math achievement
significantly increases due to the use of manipulatives.
 Is there a significant difference in amount of students’
dazing during a lecture hour among the three different
room arrangements?
 Is there a significant difference in work productivity in a
glue factory when working to a low tempo of music versus
a high tempo of music?
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8. Identifying IV and DV
 Is there a significant difference in weight loss
between those on a diet and those exercising?
 Does highest degree earned (GED, HS,college)
affect social awareness?
 Is there a significant difference in cognitive
development among infants born less than 4
pounds, 4.1-6 pounds, and 6.1-8 pounds?
 Do elementary school boys and girls differ in their
needs for social interaction?
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9. Identifying IV and DV
 A researcher has developed a new aid for
teaching 7th grade students about electric
circuits. The researcher wants to know whether
students’ knowledge of electric circuits
increases more using the aid if they
(a) explore it individually without instruction,
(b) are given written instructions about it, or
(c ) watch a demonstration of how it works.
The researcher administers a pre- and post-test
to assess students’ learning.
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10. Identifying IV and DV’S
 A company wants to investigate the
influence of three types of training
programs (coworker, consultant, self) on
employees’ job performance three months
after the programs have been completed.
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11. Categorical vs. Continuous Variables
 Categorical variables
 Take on a small set of possible values
 Typically qualitative
 Also called “qualitative” or “discrete” variables
 Examples:
Variable Category
Gender Male, female
Political party Republican, Democrat, Independent
Ethnicity African American, White, Asian, Hispanic
Parenting style Passive, Authoritarian, Authoritative
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12. Discrete vs. Continuous Variables
 Continuous variables
 Always quantitative
 Measurement
 Less to more of something
 Able to put on a continuum and quantify (assign meaningful #
to it)
 Examples:
Variable Scale (Less to more)
Age Years
Temperature FO or CO
Running time Minutes
Heart rate Beats per minute
Distance Miles, yards, meters
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13. Scales of Measurement
Categorical Continuous
Nominal Ordinal Interval Ratio
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14. Scales of Measurement
 Nominal scale
 Labels items; often meaningless
 No scale quality
Example: Male = 1 Female = 2 (dichotomous)
Example: Blue eyes = 1 Brown eyes = 2 Green eyes = 3
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15. Scales of Measurement
 Ordinal Scale
 Orders people, objects, events along some continuum
Examples:
1. Who did better on a test (rank order)
2. Likert-type rating scales (1-4, 1-5, 1-7, etc.)
3. Age transformed
20-25 years = 1
26-30 years = 2
31-35 years = 3
36-40 years = 4
41-45 years = 5
46 years and older= 6
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16. Scales of Measurement
 Interval Scale
 Intervals have the same interpretation throughout
 Example: Difference between 30 degrees and 40
degrees represents the same temperature difference
as the difference between 80 and 90 degrees.
 Not perfect. No true zero point.
 0 degrees Fahrenheit does not mean the complete
absence of temperature.
 Can’t compute ratio’s due to this fact.
 40 degrees not one-half of 80.
 80 degrees is not twice as hot as 40 degrees.
 Because no true zero value!!
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17. Scale of Measurement
 Ratio scale
 Most informative scale.
 Provides name or category for each object (numbers as
labels).
 Objects are ordered (in terms of numbers).
 Same difference at two places on the scale has the same
meaning.
 Interval scale with zero position added.
 So, can have absence of the quantity measured.
 Zero money (no money)
 Someone with 50 cents has twice as much money as
someone with 25 cents
 Age, height, weight, percentage
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18.  Complete Assignment 1: Identifying Independent
and Dependent Variable(s) and their Properties in
a Research Question
 Note cards:
 Sample vs. Population
 Descriptive vs. Inferential statistics
 Variable name vs. value
 Independent vs. dependent variable
 Types of variables (Dichotomous, Categorical,
Continuous)
 Scales of measurement (nominal, ordinal, interval,
ratio)
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