1331.0 - Statistics - A Powerful Edge!, 1996  
ARCHIVED ISSUE Released at 11:30 AM (CANBERRA TIME) 31/07/1998   
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Contents >> Stats Maths >> Organising Data - Variables

ORGANISING DATA

After collection and processing, data need to be organised to produce useful information. It helps to be familiar with some definitions when organising data. This section outlines those definitions and provides some simple techniques for organising and presenting data.

VARIABLES

Definition

The word variable is often used in the study of statistics and so it is important to understand its meaning. A variable is:

ANY TRAIT THAT IDENTIFIES DIFFERENT VALUES FOR DIFFERENT PEOPLE OR ITEMS.

Height, age, amount of income, country of birth, grades obtained at school and type of housing are examples of variables. Variables may be classified into various categories, some of which are outlined in the following pages.


NOMINAL VARIABLES

A nominal (also called categorical) variable is one that describes a name or category.

EXAMPLE

1. The method of travel to work by people in Darwin at the time of the 1996 Census was:

Method of travel to work
Number of people

CAR AS DRIVER
23,617
CAR AS PASSENGER
3,699
BICYCLE
1,335
WALKED
1,703
BUS
1,335
WORKED AT HOME
1,012
MOTOR BIKE/SCOOTER
577
TAXI
284
TRAIN
25
FERRY/TRAM
11


In this case the variable ‘method of travel to work’ is nominal because it describes a name.


NUMERIC VARIABLE

A numeric variable is one that describes a numerically measured value. However, not all variables described by numbers are numeric. For example, the age of a person is a numeric variable, but their year of birth, despite being a number, is a nominal variable.

Numeric variables may be either continuous or discrete:


CONTINUOUS VARIABLE

A variable is said to be continuous if it can take any value within a certain range. Examples of continuous variables may be distance, age or temperature.

The measurement of a continuous variable is restricted by the methods used, or by the accuracy of the measuring instruments. For example, the height of a student is a continuous variable because a student may be 1.6321748755... metres tall.
However, when the height of a person is measured, it is usually only measured to the nearest centimetre. Thus, this student’s height would be recorded as 1.63m.

Note that continuous variables are usually grouped using class intervals (explained shortly). They are grouped to make them easier to handle as part of the general process of organising data into information.


DISCRETE VARIABLE

Any variable that is not continuous is discrete. A discrete variable can only take a finite number of values within a certain range. An example of a discrete variable would be a score given by a judge to a gymnast in competition: the range is 0-10 and the score is always given to one decimal place.

Discrete variables may also be grouped. Again, this is done to make them easier to handle.

NOTE: measurement of a continuous variable is always a discrete approximation.


    ORDINAL VARIABLE

    An ordinal variable is one that can be placed in order. Numeric variables are always ordinal, while only some nominal variables are ordinal.

    1. A teacher may rank a class of students in order according to their behaviour:

    Behaviour
    Number of Students

    Excellent
    5
    Very Good
    12
    Good
    10
    Bad
    2
    Very bad
    1


    In this case the variable ‘behaviour’ is nominal and ordinal.



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