Introduction: The collection of data can be classified according to the resemblances and similarities. Classification gives expression to the similarities which may be found in the diversity of individual units. In classification of data units having common characteristic are placed in one class and in this fashion the whole data are divided into a number of classes. Even after classification, the statistical data are not fit for comparison and interpretation and need proper tabulation. The ideal classification should have the characteristics of unambiguous, stability and flexibility. The types of classification are Geographical, Chronological, Qualitative and Quantitative. In this section we shall discuss with Qualitative Data Classification.

Qualitative Data: When the data are classified according to some qualitative phenomena which are not capable of quantitative measurement like honesty, beauty, employment, intelligence, occupation, sex, literacy, etc, the classification is termed as qualitative or descriptive or with respect to attributes.

In qualitative classification the data are classified according to the presence or absence of the attributes in the given units. If the data are classified into only two classes with respect to attribute like its presence or absence among the various units, the classification is termed as simple or dichotomous.

If the data is classified into more than two classes with respect to a given attribute, it is said to be a manifold classification. For example, for the attribute intelligence the various classes may be, genius, very intelligent, average intelligent, below average and dull.
We can analyze the qualitative data with the help of the following example.
For example, the population of individuals can be classified as follows.
1. honest and dishonest
2. male and female
3. Employed and unemployed
4. Beautiful and not beautiful
               Moreover, if the given population is divided into classes on the basis of simultaneous study of the more than one attribute at a time, the classification is again termed as manifold classification.  The following flow diagram shows the classification according to the above attributes.
Qualitative Data
Quanititative and Qualitative data have the following differences.

1. Both are the classification of data.

2. Quantitative is in terms of the numbers whereas the qualitative is in terms of the attributes which are arbitrary.
One attribute gradually changes into another attribute and there is no clear cut line of demarcation.
Whenever data are classified according to attributes the point should be kept in mind and attempts must be made to define the attributes in such a manner that there is the least possibility of doubt and ambiguity.

3. In Quantitative data there are two important terms called variables and frequency, where as in qualitative data there will be only attributes as they don't involve on numbers.

4. Quantitative data can be classified into discrete and continuous series where as Qualitative data can be classified only into their arbitrary nature like, tall, short, intelligent , not intelligent, beautiful, not beautiful etc.
Example 1: The School
Qualitative:
Students are intelligent
Students are bold
Teachers are more efficient
There is friendly relationship between the students and teachers.
The building is Red in color.

Quantitative:
There are 1500 students in the school.
About 95% of the students obtain distinction every year.
There are 60 teachers in the school.
The student, teacher ratio in the school is 25 : 1

Example 2: The Hospital
Qualitative:
The hospital is located at the center of the city.
The doctors are highly qualified and more efficient.
All the doctors care the patients very well.
The nursing in the hospital is excellent.

Quantitative:
There are 120 doctors in the hospital.
The hospital has 23 departments like, Gyneacology, Dematology, Oncology, Orthopedics etc.
The hospital has about 240 nurses in the hospital.
The doctor nurse ratio is 1 : 2.