Chapter 2: Classification of Variables Flashcards
is any factor or property that a researcher measures, controls, and/or manipulates in a research study.
Variable
a variable is also called?
data item
CLASSIFICATION OF VARIABLES
- NUMERIC VARIABLES
- CATEGORICAL VARIABLES
- EXPERIMENTAL VARIABLES
- NON- EXPERIMENTAL VARIABLES
- VARIABLES ACCORDING TO THE NUMBER BEING STUDIED
variables with values that describe a measurable numerical quantity and answer the questions “how many” or “how much”
“Quantitative data”
numeric variables
NUMERIC VARIABLES:
- Continuous Variables
- DIscrete Variables
can assume any value between a certain set of real numbers.
Continuous Variables
continuous variables s also called
“interval variables”
Examples: time, age, temperature, height, weight
Continuous Variables
the values depend on the scale used.
Continuous Variables
can assume any whole value within the limits of the given variables
Discrete Variables
Examples: number of registered cars, number of business locations, number of children in the family, population of students, total number of faculty members
Discrete Variables
variables with values that describe a quality or characteristic of a data unit like “what type” or “which category”
CATEGORICAL VARIABLES
CATEGORICAL VARIABLES
- Ordinal Variables
- Nominal Variables
- Dichotomous Variables
- Polychotomous Variables
these variables can take a value which can be logically ordered or ranked
Ordinal Variables
Examples: academic grades such as A,B,C; clothing size such as X, L, M, S; and measures of attitudes like strongly agree, agree, disagree, or strongly disagree.
Ordinal Variables
variables whose values cannot be organized in a logical sequence
Nominal Variables
Examples: business types, eye colors, kinds of religion, various languages, types of learners
Nominal Variables
these variables represent only two categories
Dichotomous Variables
Examples: gender (male and female), answer (yes or no), veracity (true or false)
Dichotomous Variables
variables that have many categories
Polychotomous Variables
Examples: educational attainment (elementary, high school, college, graduate, and postgraduate), level of performance (excellent, very good, good, satisfactory, or poor)
Polychotomous Variables
EXPERIMENTAL VARIABLES :
- Independent Variables
- Dependent Variables
3, Extraneous Variables
these variables are usually manipulated in an experiment
“Manipulated or Explanatory Variable”
Independent Variables
these variables are usually affected by the manipulation of the independent variables
“Response or Predicted Variable”
Dependent Variables