variables
Extraneous variables -also known as covariate variable
- also called mediating or intervening variable, variables that are already existing during the conduct of an experiment and could influence the result of the study
Predictor variables
- changes the other variable/s in a non-experimental study
Univariate study
- only one variable is being studied
Bivariate study
- two variables are being studied
Dependent variables
- usually affected by the manipulation of independent variables, also called response or predicted variable
Criterion variables
- usually influenced by the predictor variables Example: Title of Research: Competencies of Teachers and Students' Behavior in Selected Private Schools Predictor variable: competencies of teachers Criterion variable: students' behaviour
Polyvariate study -
-more than two variables are being studied
Continuous variables
a. can assume any value between a certain set of real numbers, also called interval variables
Ordinal variables
a. can take a value which can be logically ordered or ranked. Ex: academic grades, clothing sizes
Polychotomous variables
a. variables that have many categories Ex: educational attainment (elementary, high school, college, graduate and post graduate)
Dichotomous variables
a. variables that represent only two categories Ex: gender (male or female), answer (yes or no), veracity (true or false)
Nominal variables
a. variables whose values cannot be organized in a logical sequence Ex: business types, eye colors, kinds of religion
Independent variables
usually manipulated in an experiment, also called manipulated or explanatory variable
Numeric variables
variable with values that describe a measurable numerical quantity and answer the questions "how many" or "how much", considered as quantitative data
Discrete variables
variables can only assume any whole value within the limits of the given variable
Categorical variables
variables with values that describe a quality or characteristic of a data unit like "what type" or " what category"