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Types of Variables
M
•
•
•
•
•
•
•
•
•
•
Dependent Variable
Independent Variable
Intervening/Mediating Variable
Control/Constant Variable
Interval variable
Ratio variable
Nominal/Categorical variable
Ordinal variable
Dummy variables
Extraneous Variable
Agenda
Variable
Any characteristic which is subject to
change and can have more than one
value such as age, intelligence,
motivation, gender, etc.
Dependent Variable
• Variable affected by the independent
variable
• It responds to the independent variable.
Independent Variable
• Variable that is presumed to influence
other variable
• It is the presumed cause, whereas the
dependent variable is the presumed
effect.
Example 1
You are interested in “How stress affects
mental state of human beings?”
Independent variable ----- Stress
Dependent variable ---- mental state of human
beings
You can directly manipulate stress levels in your
human subjects and measure how those stress
levels change mental state.
Example 2
Promotion affects employees’ motivation
Independent variable ----- Promotion
Dependent variable ----Employees motivation
Intervening/Mediating Variable
It is a variable whose existence is inferred
but it cannot be measured.
Example 1
Determining the effect of video clips on
learning ability of students of M.Phil.
The association between video clips and learning ability
needs to be explained.
Other variables intervene
Such as anxiety, fatigue, motivation, improper diet, etc.
It is caused by the independent variable and is
itself a cause of the dependent variable.
Intervening/Mediating Variable
(Contd.)
Example 2
Higher education typically leads to
higher income
•Higher education----(independent variable)
•Higher income----(dependent variable)
•Better occupation---- intervening variable
It is causally affected by education and itself affects
income.
Control/Constant variable
• It is variable that is NOT allowed to be
changed unpredictably during an
experiment.
• As they are ideally expected to remain the
same, they are also called constant variables.
Example
An example of a constant variable is the voltage
from a power supply.
If you are examining “How electricity affects
experimental subjects” you should keep the
voltage constant, otherwise the energy supplied
will change as the voltage will be changed.
Interval Variable
• Interval variables have a numerical value
• These have order and equal intervals.
• They allow not only to rank order the items that
are measured but also to quantify and compare
the magnitudes of differences between them.
Example
Suppose you have a variable such as monthly
income that is measured in rupees, and we have
three people who make
•Rs. 10,000
• Rs. 15,000 and
•Rs. 20,000
Ratio Variable
A ratio variable is similar to an interval variable
with one difference: the ratio makes sense.
Example
• Let’s say respondents were being surveyed about their
stress levels on a scale of 0-10.
• A respondent with a stress level of 10 should have
twice the stress experienced as a respondent who
selected a stress level of 5.
Age, height, and weight are also good examples of ratio
variables. Someone who is 6’.0” tall is twice as tall as
someone who is 3’.0” tall.
Nominal/Categorical Variable
• They can be measured only in terms of whether the
individual items belong to certain distinct categories
• We cannot quantify or even rank/order the categories:
• Nominal data has no order
• One cannot perform arithmetic (+, -, /, *) or logical
operations (>, <, =) on the nominal data.
Example
Gender:
(Dichotomous Variable)
1. Male
2. Female
Marital Status: 1. Unmarried
2. Married
3. Divorcee
4. Widower
Ordinal Variable
•
•
•
•
An ordinal variable is a nominal variable, but its different states
are ordered in a meaningful sequence.
Ordinal data has order but the intervals between scale points may
be uneven.
Because of lack of equal distances, arithmetic operations are
impossible, but logical operations can be performed on the
ordinal data.
A typical example of an ordinal variable is the socio-economic
status of families.
We know 'upper middle' is higher than 'middle' but we
cannot say 'how much higher'.
Example
A questionnaire on the time involvement of scientists in the 'perception
and identification of research problems'.
The respondents were asked to indicate their involvement by selecting one
of the following codes:
1 = Very low or nil
2 = Low
3 = Medium
4 = Great
5 = Very great
Here, the variable 'Time Involvement' is an ordinal variable with 5 states.
Dummy Variable
A qualitative variable can be transformed into
quantitative variable(s), called dummy variable.
Description
Gender
Variable
gender
Dummy Variable
Job Category JOBCAT
Dummy Variable
D1-Job
Category
Clerical---1
otherwise 0
Code
f- female
m-male
D-Gender
Female---1
otherwise 0
1-Clerical
2-Coustodian
3-Manager
D2-Job
Category
Custodian---1
otherwise 0
Example
Extraneous Variable
Extraneous variables are undesirable variables
that influence the relationship between the
variables an experimenter is examining.
An educational psychologist has developed a new learning
strategy and is interested in examining the effectiveness of
this strategy.
The experimenter randomly assigns students into two groups. All of
the students study text materials on a biology topic for thirty
minutes. One group uses the new strategy and the other uses a
strategy of their choice.
Then all students complete a test over the materials.
Extraneous variable ------ pre-knowledge of the biology
topic
Example
variables. Independent and Dependent variables

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variables. Independent and Dependent variables

  • 2. • • • • • • • • • • Dependent Variable Independent Variable Intervening/Mediating Variable Control/Constant Variable Interval variable Ratio variable Nominal/Categorical variable Ordinal variable Dummy variables Extraneous Variable Agenda
  • 3. Variable Any characteristic which is subject to change and can have more than one value such as age, intelligence, motivation, gender, etc.
  • 4. Dependent Variable • Variable affected by the independent variable • It responds to the independent variable.
  • 5. Independent Variable • Variable that is presumed to influence other variable • It is the presumed cause, whereas the dependent variable is the presumed effect.
  • 6. Example 1 You are interested in “How stress affects mental state of human beings?” Independent variable ----- Stress Dependent variable ---- mental state of human beings You can directly manipulate stress levels in your human subjects and measure how those stress levels change mental state.
  • 7. Example 2 Promotion affects employees’ motivation Independent variable ----- Promotion Dependent variable ----Employees motivation
  • 8. Intervening/Mediating Variable It is a variable whose existence is inferred but it cannot be measured.
  • 9. Example 1 Determining the effect of video clips on learning ability of students of M.Phil. The association between video clips and learning ability needs to be explained. Other variables intervene Such as anxiety, fatigue, motivation, improper diet, etc.
  • 10. It is caused by the independent variable and is itself a cause of the dependent variable. Intervening/Mediating Variable (Contd.)
  • 11. Example 2 Higher education typically leads to higher income •Higher education----(independent variable) •Higher income----(dependent variable) •Better occupation---- intervening variable It is causally affected by education and itself affects income.
  • 12. Control/Constant variable • It is variable that is NOT allowed to be changed unpredictably during an experiment. • As they are ideally expected to remain the same, they are also called constant variables.
  • 13. Example An example of a constant variable is the voltage from a power supply. If you are examining “How electricity affects experimental subjects” you should keep the voltage constant, otherwise the energy supplied will change as the voltage will be changed.
  • 14. Interval Variable • Interval variables have a numerical value • These have order and equal intervals. • They allow not only to rank order the items that are measured but also to quantify and compare the magnitudes of differences between them.
  • 15. Example Suppose you have a variable such as monthly income that is measured in rupees, and we have three people who make •Rs. 10,000 • Rs. 15,000 and •Rs. 20,000
  • 16. Ratio Variable A ratio variable is similar to an interval variable with one difference: the ratio makes sense.
  • 17. Example • Let’s say respondents were being surveyed about their stress levels on a scale of 0-10. • A respondent with a stress level of 10 should have twice the stress experienced as a respondent who selected a stress level of 5. Age, height, and weight are also good examples of ratio variables. Someone who is 6’.0” tall is twice as tall as someone who is 3’.0” tall.
  • 18. Nominal/Categorical Variable • They can be measured only in terms of whether the individual items belong to certain distinct categories • We cannot quantify or even rank/order the categories: • Nominal data has no order • One cannot perform arithmetic (+, -, /, *) or logical operations (>, <, =) on the nominal data.
  • 19. Example Gender: (Dichotomous Variable) 1. Male 2. Female Marital Status: 1. Unmarried 2. Married 3. Divorcee 4. Widower
  • 20. Ordinal Variable • • • • An ordinal variable is a nominal variable, but its different states are ordered in a meaningful sequence. Ordinal data has order but the intervals between scale points may be uneven. Because of lack of equal distances, arithmetic operations are impossible, but logical operations can be performed on the ordinal data. A typical example of an ordinal variable is the socio-economic status of families. We know 'upper middle' is higher than 'middle' but we cannot say 'how much higher'.
  • 21. Example A questionnaire on the time involvement of scientists in the 'perception and identification of research problems'. The respondents were asked to indicate their involvement by selecting one of the following codes: 1 = Very low or nil 2 = Low 3 = Medium 4 = Great 5 = Very great Here, the variable 'Time Involvement' is an ordinal variable with 5 states.
  • 22. Dummy Variable A qualitative variable can be transformed into quantitative variable(s), called dummy variable.
  • 23. Description Gender Variable gender Dummy Variable Job Category JOBCAT Dummy Variable D1-Job Category Clerical---1 otherwise 0 Code f- female m-male D-Gender Female---1 otherwise 0 1-Clerical 2-Coustodian 3-Manager D2-Job Category Custodian---1 otherwise 0 Example
  • 24. Extraneous Variable Extraneous variables are undesirable variables that influence the relationship between the variables an experimenter is examining.
  • 25. An educational psychologist has developed a new learning strategy and is interested in examining the effectiveness of this strategy. The experimenter randomly assigns students into two groups. All of the students study text materials on a biology topic for thirty minutes. One group uses the new strategy and the other uses a strategy of their choice. Then all students complete a test over the materials. Extraneous variable ------ pre-knowledge of the biology topic Example