Introduction to Variables

Mass Communication Research:

A variable is a characteristic, number, or quantity that increases or decreases over time, or takes different values in different situations. There are many types of variables but two of them are basic.

Basic Types of Variables

There are two basic types of Variables which are:

1. Independent variable
2. Dependent variable

• Independent variable

  An independent variable (sometimes called an experimental or predictor variable) is a variable that is being manipulated in an experiment in order to observe the effect this has on a dependent variable. 

Example:

Revision time and intelligence (i.e., independent variables) may (or may not) cause a change in the test mark (i.e., the dependent variable), the reverse is implausible. 

• Dependent variable

The dependent variable is simply that; a variable that is dependent on an independent variable.

Example:

Test mark (i.e. the dependent variable) that a student achieves is dependent on revision time and intelligence.

Categorical Variables:

Categorical variables are also known as qualitative (or discrete) variables. These categorical variables can be further classified as being 

•Nominal

•Dichotomous

•Ordinal variables.

• Nominal Variables

Nominal variables have two or more categories.

Example:

It includes questions like hair color Black, Blond, Brown, Red, etc. Blood Group A, B, AB, O, etc.

• Dichotomous Variables 

Dichotomous variables are nominal variables that have just two categories. Dichotomous variables are designed to give you an either/or response.

Example:

 You are either male or female. You either like watching television (i.e., you answer YES) or you don’t (i.e., you answer NO).

• Ordinal Variables

Just like nominal variables, ordinal variables have two or more categories. However, unlike nominal variables, ordinal variables can also be ordered or ranked (i.e., they have levels)

Example:

If someone asks Do you like watching television? Then and could be Most of the time, Sometimes, Hardly ever.

Other Types:

• Confounding Variables

A variable that obscures the effects of another variable. 

Example:

If one elementary reading teacher used a phonics textbook in her class and another instructor used a whole language textbook in his class, and students in the two classes were given achievement tests to see how well they read, the independent variables (teacher effectiveness and textbooks) would be confounded. There is no way to determine if differences in reading between the two classes were caused by either or both of the independent variables.

• Intervening Variables

A variable that explains a relation or provides a causal link between other variables. Also called by some authors “mediating variable” or “intermediary variable.” 

Example:

The statistical association between income and longevity needs to be explained because just having money does not make one live longer. Other variables intervene between money and long life. People with high incomes tend to have better medical care than those with low incomes. Medical care is an intervening variable. It mediates the relation between income and longevity.

• Latent variable

 An underlying variable that cannot be observed. It is hypothesized to exist in order to explain other variables, such as specific behaviors that can be observed. 

Example:

 If we observe the voting records of members of the House of Representatives on spending bills for the military, food stamps, law enforcement, and promoting business investment, we might find underlying patterns that could be explained by postulating latent variables such as conservatism and liberalism.

• Mediating variable 

Synonym for intervening variable. 

Example:

Parents transmit their social status to their children directly, but they also do so indirectly, through education:by the way of  Parent’s status , child’s education , child’s status.

• Manifest variable

 An observed variable assumed to indicate the presence of a latent variable. Also known as an indicator variable. 

Example:

We cannot observe intelligence directly, for it is a latent variable. We can look at indicators such as vocabulary size, success in one’s occupation, IQ test score, ability to play complicated games (e.g., bridge) well, writing ability, and so on.