Page 116 - DLIS401_METHODOLOGY_OF_RESEARCH_AND_STATISTICAL_TECHNIQUES

Unit 7: Data Analysis and Interpretation

In Table 7.3, number of schools have been shown according to the enrolment of students in Notes
the school. Schools with enrolment varying in a specified range are grouped together, e.g.
there are 15 schools where the students enrolled are any number between 51 and 100. As the
grouping is based on numbers, such data are called Numerical or Quantitative Data. Thus,
numerical or quantitative data result from counting or measuring. We frequently come across
numerical data in newspapers, advertisements etc. related to the temperature of the cities,
cricket averages, incomes, expenditures and so on.

Task Write an essay on quantitative analysis.

Continuous and Discrete Data
Numerical or quantitative data may be continuous or discrete depending on the nature of the
elements or objects being observed.

Let us consider the Table 7.4 depicting the heights of students of a class.

Table 7.4 Heights of Students of a Class
Height No. of Students
4’8"–4'10" 2
4'10"–5'0" 2

5'0"–5'2" 5
5'2"–5'4" 8
5'4"–5'6" 12
5'6"–5'8" 10
5’8"–5’10" 2
Total 41
Table 7.4 gives the data pertaining to the heights of students of a class. Here the element under
observation is the height of the students. The height varies from 4' 8" to 5' 10". The height of
an individual may be anywhere from 4' 8" to 5'10". Two students may vary by almost zero inch
height. Even if we take two adjacent points, say 4' 8.00" and 4' 8.01" there may be several
values between the two points. Such data are called Continuous Data, as the height is continuous.
Continuous Data arise from the measurement of continuous attributes or vdriables, in which
individual may differ by amounts just approaching zero. Weights and heights of children;
temperature of a body; intelligence and achievement level of students, etc. are the examples
of continuous data.
Let us consider Table 7.3 showing the number of students enrolled and the number of schools
according to enrolment. Let us,consider the enrolment of 2 schools as 60 and 61. Now in
between 60 and 61, there cannot be any number, as the enrolment will always be in whole
numbers. Thus there is a gap of one unit from 60 to 61. Such data, where the elements being
observed have gaps are called Discrete Data.

Discrete Data are characterised by gaps in the scale, for which no real values may ever be
found. Such data are usually expressed in whole numbers. The size of a family, enrolment of
children, number of books etc. are the examples of discrete data. Generally data arising from
measurement are continuous, while data arising from counting or arbitrary classification are
discrete.

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