Agriculture Reference
In-Depth Information
color (e.g., red, green), and taste (e.g., sweet, sour,
bitter) which cannot be measured as such but can be
grouped, ranked, and categorized; these are known
as
which means taking out any plant from the field
of a particular variety, its height will be within
the range of 60-90 cm.
qualitative characters
/
variables
. The qualitative
variables are also known as
.Eachvari-
able or characteristic is generally associated with
the chance factor. In statistical sciences, a
researcher is interested in studying not only the
variable but also their probability distributions.
As such, the variable with chance/probability
factor—the variate—is of much interest rather
than simply a variable. Thus, the variate is defined
as variable with chance or probability factor. Rain-
fall is a variable which varies over days (say), but
when it is associated with probability distributions,
then it becomes a variate.
In literature, variables have been categorized
into different types in accordance with its nature,
purpose, use, etc. One can find the following
types of variables in different literatures, though
the types are neither exhaustive nor exclusive
rather sometimes they are overlapping:
1. Continuous variable
2. Discrete variable
3. Dependent variable
4. Independent variable
5. Explanatory variables
6. Extraneous variable
7. Stimulus variable
8. Control variable
9. Dummy variable
10. Preference variable
11. Multiple response variable
12. Target variable
13. Weight variable
14. Operationally defined variable
attributes
5.1.2 Discrete Variable
A discrete variable is one which takes only an
integer value within a given range. For example,
the number of grains per panicle of a particular
variety of paddy varies between 40 and 60 grains.
This means if one takes out any panicle of that
particular variety, the number of grains in it will
take any value within this range. But one cannot
expect that the panicle taken at random should
have a number of grains 50.6 or like that; it will
be 50 or 51.
5.1.3 Dependent Variable
A dependent variable is a type of variable whose
values are dependent on the values taken by the
other variables and their relationship. Generally
in relational studies, a variable is influenced/
affected by other related variables. In a produc-
tion function analysis, there exists a functional
relationship between the output and the factors of
production. Here the output is considered as
dependent variable which depends on the factors
of production like land, labor, capital, and man-
agement. In socioeconomic studies, the adoption
index (dependent variable) with respect to the
adoption of a particular technology may depend
on a number of socioeconomic factors like age
(
x
1
), caste (
x
2
), education (
x
3
), family type (
x
4
),
5.1.1 Continuous Variable
social status (
x
5
), economic conditions (
x
6
), area
x
7
), and the size of holding
under cultivation (
A continuous variable can take any value within
a given range. Plant height, length of panicle,
length and breadth of leafs, heights of different
groups of people, etc., are the examples of a
continuous character/variable. These variables
can take any value for the respective range. If
one says that the plant height of a particular
variety of paddy varies from 60 to 90 cm,
(
x
8
). Thus, one can write
y ¼ f
(
x
1
,
x
2
,
x
3
,
x
4
,
x
5
,
x
6
,
x
7
,
x
8
). In this example,
y
is the dependent
variable and
x
1
...
x
8
are the independent
variables. One can use a functional relationship
to predict the values of a dependent variable for a
given set of values of the variables
x
1
...
x
8
.
As such,
y
is also known as predicted variable
and
x
1
...
x
8
are known as predictor variables.
