Agriculture Reference
In-Depth Information
respondent could score more than one category
out of the following options: (1) talking to people
at distant places, (2) using GPS for daily life
activities, (3) using camera for getting records,
(4) listening to music, (5) used for simple
calculations, (6) using as a miniature form of
computers, etc. To a user talking to people at
different places along with listening to music
may be of equal and top priority. To others, it
may be the talking to people at distant places
along with the use of miniature form of computers
be of equal or top priority. Thus, in both cases, the
user has no preference to select one at topmost
priority rather than other ones. As such, there are
multiple responses to the query: why a user likes
to have a mobile?
variables are defined and measured within the
framework of a research study. If one wants to
test the performance of driving, then before tak-
ing the variables to score the performance of a
driver, it is required to have clear-cut a definition
of “a driver”—what do we mean by driver?
5.1.14.1 Criteria for the Selection
of Variables
Having formulated the problem of a research
work, the objective and the specific objective of
the studies and the hypothesis to be tested and a
guideline or an abstract idea about the type of
variables to be studied become visible to a
researcher. At the first instance, a researcher
investigates what is the information required
and what is the information available from the
study—experimental or nonexperimental. In fact
a researcher at this point of time will be among
the host of variables. But the most pertinent thing
is that how many variables are available and
how many variables are required to be studied
under a framework of a study (under the given
time, money, technical experts, instrumental
availability, etc.). Generally while selecting a
variable, a researcher should keep in mind the
following points: (1) objective of the study, (2)
specific objective of the study, (3) hypothesis to
be tested, (4) variables which should be mutually
exclusive (nonoverlapping), (5) variables which
should be clearly understood by a researcher, (6)
techniques that are available or to be developed
to measure a variable, (7) the number of variables
that should not be too many or too few, and (8)
availability of time and resources to researchers.
The variables to be selected should be guided or
commensurated with the objective and specific
objective of a research program. The variable to
be included must be clearly defined; any ambi-
guity in defining the variables may jeopardize the
findings of a research program. The variables to
be selected must be related with the hypothesis to
be tested in a study, and must be nonoverlapping
in nature. The variable which could not be
measured with sufficient level of accuracy or
which measurement availability of
5.1.12 Target Variable
A target variable is almost synonymous to that of
a dependent variable in a classical regression
analysis. The main objective is to target a vari-
able (predicted variable) whose value (s) is
required to be predicted taking help of the values
of the other variables and also the relational
form.
5.1.13 Weight Variable
A weight variable specifies the weightage to be
given to different data sets/subsets. A weight vari-
able may be continuous or discrete in nature. In a
given data set, if “0” is assigned to any row of
data, then that particular row could be ignored. On
the other hand, a weightage given to rows 1, 2, 3,
etc., means the rows concerned have different
importance.
5.1.14 Operationally Defined Variable
Before conducting any experiment, it is impera-
tive to have a firm operational definition for all
the variables under consideration. An operational
definition of a certain variable describes how
technical
staff is in dearth may be avoided.
