Practical No : 2 / प्रात्यक्षिक क्र : २
Data Organization / क्षिदा (साांख्यिकीय माक्षिती) सांघटन
Introduction / प्रस्तािना : After you collect and review data, you should check whether it
really makes sense. You need to check how much of the collected data is really useful.
This step is known as data organization. The way to do that is two-fold
(1) Organize the data in a visual manner
(2) Organize the collected data into tables according to various variables or items as per
your needs.
Objectives / उक्षिष्टे : To understand data organization for the classification collected data
Data is considered as information which is based on facts or statistics collected and
recorded for particular purpose or analysis. These are various types of data in geography
(climate, population, migration).
Definitions
Data organization refers to the process of systematic arrangement of data for simplified
and convenient uses.
After the collection of data review is required and it should be checking how much of the
collected data is useful. This process is called as data organization.
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A. Grouped Data / अ. सांघक्षटत क्षिदा
Income Categories No of people who have incomes in these categories
0 - 10000 20
10000 - 20000 25
20000 - 30000 28
30001 - 40000 20
40000 and more 7
Total 100
Data organization with examples
From the following set of data we have to organize the data into groups with an interval
of 5.
25, 18, 20, 28, 18, 34, 24, 27, 21, 31, 26, 26, 38, 28, 20, 24, 28, 33, 18, 32
Conclusion / क्षनष्कर्ष :
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B. Grouped Data / आ. सांघक्षटत क्षिदा
Here is an example of survey of monthly income of people in an area. The data is of 100
people and after the classification the classified data will look like
Example of grouped data
Income classes No. of people having income in different income classes
0 - 15000 15
15000 - 30000 15
30000 - 45000 35
45000 - 60000 15
60000 and above 20
Total 100
Conclusion / क्षनष्कर्ष : In the above example, we cannot list all of the income values as it
is or in an ungrouped form because the count of surveyed people is more. Therefore, in
this case, we need to group the data into respective clauses. This form of representation is
very easy and useful to analyze and to interpret the result.
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C. Ungrouped Data / इ. असांघक्षटत क्षिदा
Items Quantity Items Quantity
Basmati Rice 1 kg Coriander Seeds 100 gms
Kolam Rice 5 kg Pepper 100 gms
Indrayani Rice 10 kg Clove 100 gms
Lokvan Wheat 10 kg Coconut Oil ¼ liters
Sihor Wheat 10 kg Groundnut Oil 2 liters
Pearl Millet 5 kg Soybean Oil 2 liters
Sorghum 5 kg Sesame Oil 1 liters
Pigeon Pea 2 kg Beans ¼ kg
Bengal Gram 2 kg Black-eyed Peas ¼ kg
Split Black Gram 1 kg Red Lentils Pulse ¼ kg
Red Lentils Dal 1 kg White Gram ¼ kg
Soap 10 Green Pea ¼ kg
Washing Powder ½ kg Black Peas ¼ kg
Liquid Soap 1 kg
Categories Categories Categories Categories
Groceries Species Stationery Electricity
Sugar Red chilies Pencils Tube light
Wheat Pepper Notebooks
Jawar Envelopes Categories
Coconut oil Categories Vegetables Soaps and detergents
Rice Beverages Coriander Liquid soap
Soybean oil Coffee Lemons Sunlight soap
Groundnut oil Tea Potato Hamam soap
Horlicks Onion
Conclusion / क्षनष्कर्ष :
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D. Ungrouped Data / ई. असांघक्षटत क्षिदा
Here is an example of survey of monthly income of people in an area. The data is of only 10
persons.
Person Income in Rs.
A 8,000
B 10,000
C 9,000
D 11,000
E 14,000
F 16,000
G 19,000
H 18,000
I 20,000
J 12,000
Conclusion / क्षनष्कर्ष :
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