PR 2 (LESSON 3) - VARIABLES

VARIABLES

A measurable characteristic that varies. It may change from group to group, person to person, or even within one person over time. (lingustics.byu.du)

Subong & Beldia (2015)

stated that variables can be classified according to Functional Relationships, according to Continuity of Values, and according to Scale of Measurement.

INDEPENDENT VARIABLE

variable that is presumed to influence other variable;

the predictor variable

the presumed cause

CALMORIN & CALMORIN (1995)

“The stimulus variable which is chosen by the researcher to determine its relationship to an observed phenomenon”

DEPENDENT VARIABLE

variable affected by the independent variable

criterion variable

responds to the independent variable

IV AND DV

What are the variables according to FUNCTIONAL RELATIONSHIPS

MODERATOR VARIABLE

It is the factor which is measured, manipulated, or selected by the experimenter to discover whether or not it modifies the relationship of the independent variable to an observed phenomenon. Subong & Beldia (2005)

IT ONLY AFFECTS THE IV

CONTROL VARIABLE

It is a variable that can be controlled or neutralized by the researcher by eliminating or removing the variable. Calmorin & Calmorin (1995)

Another type of variable that researchers measure for the purposes of eliminating it

also known as the extraneous variable

INTERVENING VARIABLE

It is a variable that interferes with the IV and DV, but its effects can either strengthen or weaken the IV and DV. Calmorin & Calmorin (1995)

The variable that "stands between" the independent and dependent variable.

exercises an influence on the dependent variable apart from the independent variable.

INTERVAL AND RATIO

2 CONTINUOUS VARIABLES

NOMINAL AND ORDINAL

2 DISCRETE VARIABLES

CONTINUOUS AND DISCRETE

2 VARIABLES ACCORDING TO CONTINUITY OF VALUES

CONTINUOUS VARIABLE

A variable that can take infinite number on the value that can occur within a population. Its values can be divided into fractions.

Examples: Age, Height

DISCRETE VARIABLE

Variables that cannot be expressed in decimals (Subong & Beldia, 2005)

Example: Number of people, number of floors

DISCRETE VARIABLE

Also known as Categorical or Classificatory Variable

Any variable that has a limited number of distinct values and which cannot be divided into fractions.

Examples: sex, blood group, number of children in the family

Number of printing mistakes in a book

Number of road accidents in New Delhi.

Number of siblings of an individual.

NOMINAL, ORDINAL, INTERVAL, RATIO

FOUR SCALES OF MEASUREMENT

NOMINAL VARIABLE

NAME WITHOUT ORDER

When measurement distinguishes responses into attributes or categories that comprise a variable.

It is a variable with no quantitative value.

It’s another name for a category

It has two or more categories but does not imply ordering of cases.

NOMALIS

Nominal is from the Latin ________, which means “pertaining to names”.

DICHOTOMOUS

A sub-type of nominal scale with only two categories.

Example: Male/Female

NOMINAL VARIABLE

Data that consist of names, labels, or categories only

The data cannot be arranged in an ordering scheme

Numbers or symbols are used to classify an object or person to identify the group they belong.

NOMINAL VARIABLE

Examples: hair color, religion, type of living accommodation, gender

ORDINAL VARIABLE

NAME WITH ORDER

Data contain the properties of a nominal level

The data can be arranged in an ordering or rank

The difference between the values of the data cannot be determined. The interval is meaningless.

ORDINAL VARIABLE

Examples: The Likert Scale, Level of Agreement, Time of Day, Political Orientation

INTERVAL VARIABLE

Data contain the properties of ordinal level.

Data values can be ranked

The difference between the values of data are of known sizes

The interval between the values has meaning

The “zero” does not imply the absence of characteristics

The ratio of data values are meaningless

Is a measurement where the difference between two value does have a meaning.

RATIO VARIABLE

it has the characteristics of the three other type of measurements, the additional characteristics that it has is the existence of a true zero.

Data contain the properties of interval level

The “zero” indicated the absence of the characteristics under consideration

The ratio of data values has meaning.

Examples: Distance, Age, Weight, Height, Number of Children

Fills a void in the existing body of knowledge

Suggests improvements for practice

Informs policy debates

IMPORTANCE OF QUANTITATIVE RESEARCH