1. Descriptive methods
• After collection and editing of data, the first step
towards further processing the same is
classification
• Classification is the grouping of related facts into
classes
• Facts in one class differ from those of the other
• Sorting facts based on one basis of classification
and on another basis is called as cross classification
2. • When students submit application in a college ,they
submit application to the office
• The application form contains information such as
performance in previous examinations, date of
birth, gender, nationality, etc.,
• If one is interested in finding how many 1st, 2nd and
3rd class students have joined the college, one may
find out how by looking into every form and note
the details
• Then they may conclude like out of 1000 students,
50 had first class, 800 second class and 150 third
class
3. • Process with the help of which this
information in a summary form is obtained is
called data classification
4. Objects of classification
• To condense the mass of data in such a manner that
similarities and dissimilarities can be readily
apprehended
• Millions of figures can thus be arranged in few
classes having common features
• To facilitate comparison
• To pinpoint most significant features of data at a
glance
• To give prominence to important information while
dropping out unnecessary elements
• To enable a statistical treatment of the material
collected
7. Geographic classification
Geographic region
South North Northeast East Central Southwest Northwest
Parti
cipants
13,128 13,938 11,989 13,823 20,991 8,388 15,801
Diabetes
prevalen
ce
n (%)
1,461
(11.1)
2,185
(15.7)
1,181 (9.9)
1,972
(14.3)
2,852
(13.6)
1,155 (13.8) 1,431 (9.1)
9. Qualitative classification
• Data are classified on the basis of some attribute or
quality such as gender, colour of hair, literacy, religion
etc.,
• In this type of classification, attribute cannot be
measured
• One can find whether it is present or absent
• Attribute – population
• When one attribute is studied, 2 classes are formed
• One possesses the attribute, other not possessing it
• Simple classification- nominal data, dichotomous
urban rural
10. • Instead of forming only 2 classes, we further divide
the data on the basis of some attributes, to form
several classes, classification is manifold
Population
males females
literates Iliterates
literates Iliterates
