Page 51 - DMGT209_QUANTITATIVE_TECHNIQUES_II

Quantitative Techniques-II

Notes 3.3 Variables

You won’t be able to do very much in research unless you know how to talk about variables.

3.3.1 Meaning

A variable is any entity that can take on different values. OK, so what does that mean? Anything
that can vary can be considered a variable.

Example: Age can be considered a variable because age can take different values for
different people or for the same person at different times.
Similarly, country can be considered a variable because a person’s country can be assigned a
value.

!
Caution Variables aren’t always ‘quantitative’ or numerical. The variable ‘gender’ consists
of two text values: ‘male’ and ‘female’. We can, if it is useful, assign quantitative values
instead of (or in place of) the text values, but we don’t have to assign numbers in order for
something to be a variable.
It’s also important to realize that variables aren’t only things that we measure in the traditional
sense. For instance, in much social research and in program evaluation, we consider the treatment
or program to be made up of one or more variables (i.e., the ‘cause’ can be considered a variable).
An educational program can have varying amounts of ‘time on task’, ‘classroom settings’, ‘student-
teacher ratios’, and so on. So even the program can be considered a variable (which can be made
up of a number of sub-variables).

3.3.2 Attribute

An attribute is a specific value on a variable. For instance, the variable sex or gender has two
attributes: male and female. Or, the variable agreement might be defined as having five attributes:
1. Strongly disagree
2. Disagree

3. Neutral
4. Agree
5. Strongly agree

Did u know? What is the difference between attributes and variables?
In contrast to variables, which are intended for bulk data, attributes are intended for
ancillary data, or information about the data. The total amount of ancillary data associated
with a net CDF object, and stored in its attributes, is typically small enough to be memory-
resident. However variables are often too large to entirely fit in memory and must be
split into sections for processing.

Another difference between attributes and variables is that variables may be multidimensional.
Attributes are all either scalars (single-valued) or vectors (a single, fixed dimension).

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