1.7 Glossary of Terms
Statistics :

Statistics is the use of data to
help the decision maker to reach better decisions.

Data :

It is any group of measurements
that interests us. These measurements provide information
for the decision maker. (I) The data that reflects nonnumerical
features or qualities of the experimental units, is
known as qualitative data. (ii) The data that possesses
numerical properties is known as quantitative data.

Population:

Any well defined set of objects
about which a statistical enquiry is being made is called
a population or universe.
The
total number of objects (individuals) in a population
is known as the size of the population. This may be
finite or infinite.


Individual : 
Each object belonging
to a population is called as an individual of the population.


Sample:

A finite set of objects drawn from the population
with a particular aim, is called a sample.
The total number of
individuals in a sample is called the sample size.


Characteristic:

The information required from an individual,
from a population or from a sample, during the statistical enquiry
(survey) is known as the characteristic of the individual. It
is either numerical or nonnumerical. For e.g. the size of shoes
is a numerical characteristic which refers to a quantity, whereas
the mother tongue of a person is a nonnumerical characteristic
which refers to a quality. Thus we have quantitative and qualitative
types of characteristics. 
Variate:

A quantitative characteristic of an individual
which can be expressed numerically is called a variate or a
variable. It may take different values at different times, places
or situations. 

Attribute:

A qualitative characteristic of an individual
which can be expressed numerically is called an attribute. For
e.g. the mothertongue of a person, the color of eyes or the
color of hair of a person etc. 

Discrete
variate :

A variable that is not capable of assuming all
the values in a given range is a discrete variate. 

Continuous
Variate :

A variate that is capable of assuming all the
numerical values in a given range, is called a continuous variate.
Consider two examples carefully, viz. the number of students
of a class and their heights. Both variates differ slightly,
in the sense that, the number of students present in a class
is a number say between 0 and 50; always a whole number. It
can never be 1.5, 4.33 etc. This type of variate can take only
isolated values and is called a discrete variate. On the other
hand heights ranging from 140 cm to 190 cm can take values like
140.7, 135.8, 185.1 etc. Such a variate is a continuous variate. 