ployee’s salary can be framed in the following
ways— idea about various measures of descriptive anal-
ysis to be used for various types of scales.
• According to you, how is your salary? Good/
Bad (Nominal scale) Once the data description is done inferential sta-
tistics plays a role to test hypothesis. It means
some inferences can be drawn about some pop-
ulation based on the observation of a small sam-
ple. For example a research on work life balance
of Indian working women does not need the en-
tire Indian working women to be studied, it can
be done by taking a sample consisting of small
number of females who are working in various
sectors in a geographical area. Hypothesis test-
ing is utilized to do the inferences. Hypothesis
is a formal statement of explanation stated in
a testable form. Hypotheses are tested to draw
a conclusion about population or about depend-
ency of variables. Depending on the number of
variables to be studied, there types of statistical
analysis are there—
• Please indicate your level of salary. Very High
/ High / Moderate / Low. (Ordinal Scale)
• Indicate your salary level on a scale of 1-10.
(Interval Scale)
Very Low Very High 1 10
• What is your gross salary in Indian rupee per
month? (Ratio Scale)
Before elaborating on why so much importance
is given on framing any question in different type
of scale, let’s have some idea about the various
types of data analysis.
Most basic type of statistical analysis is “Descrip-
tive analysis”, which is used to summarise the
responses from large number of respondents
in a few simple statistical measures. Data can
be described in terms of “Frequency”, “Central
Tendency’ and “Statistical Distribution” followed
by a set of data. Mean, median, mode, range,
standard deviation, variance are widely used
in descriptive statistics. Data description can be
done with the help of tabulation, graphs, charts
and cross tabulation. Mean, median and mode
gives an idea about the central tendencies of the
data and range and standard deviation depict
the variability of data. Following table gives an
• Univariate statistical analysis- hypothesis in-
volving only one variable. E.g. Working women
in IT sector are highly stressed.
• Bivariate statistical analysis- tests hypotheses
involving two variables. E.g. Flexible timing of
work reduces stress level of female workers.
• Multivariate statistical analysis- tests hy-
potheses involving more than two variables.
E.g. Flexible timing of work, number of family
m