Machine Learning
These are nominal variables which have logical order.
Examples include team ranks in cricket or football, merit list of
students appearing for grade students.
These are variables which can take can any value on the
measurement scale example includes pitch of voice which can
take any possible value within the range.
These are variables which can take fixed values in range. For
example, number of customers in a bank.
Yes, based upon the motive of study, it is possible to convert
discrete values to continuous and vice versa, for example, Level
of water in the tank can take any value in the range and as such a
continuous variable.
But we can approximate the same to three different levels like empty, full, or half empty and this now becomes discrete in nature.
But we can approximate the same to three different levels like empty, full, or half empty and this now becomes discrete in nature.
These are variables which are grouped on interval. Example is
age can be divided in range like 10-20, 20-30 and so on and,
person with particular age would be placed in one of the above
groups. When intervals are equal, they represent difference in
equal property being measured.
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