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Chapter 3: Organisation of Data
You also came to know the difference between census and sampling. In this chapter, you will know how the data, that you collected, are to be classified. The purpose of classifying raw data is to bring order in them so that they can be subjected to further statistical analysis easily. Have you ever observed your local junk dealer or kabadiwallah to whom you sell old newspapers, broken household items, empty glass bottles, plastics, etc?
He purchases these things from you and sells them to those who recycle them. But with so much junk in his shop it would be very difficult for him to manage his trade, if he had not organised them properly. To ease his situation he suitably groups or “classifies” various junk. He puts old newspapers together and ties them with a rope.
Then collects all empty glass bottles in a sack. He heaps the articles of metals in one corner of his shop and sorts them into groups like “iron”, “copper”, “aluminium”, “brass” etc., and so on. In this way he groups his junk into different classes — “newspapers, “plastics”, “glass”, “metals” etc. — and brings order in them. Once his junk is arranged and classified, it becomes easier for him to find a particular item that a buyer may demand.
Likewise when you arrange your schoolbooks in a certain order, it becomes easier for you to handle them. You may classify them according to junk according to the markets for reused goods. For example, under the group “Glass” he would put empty bottles, broken mirrors and windowpanes, etc. Similarly when you classify your history books under the group “History” you would not put a book of a different subject in that group.
Otherwise the entire purpose of grouping would be lost. Classification, therefore, is arranging or organising things into groups or classes based on some criteria. Like the kabadiwallah’s junk, the unclassified data or raw data are highly disorganised. They are often very large and cumbersome to handle. To draw meaningful conclusions from them is a tedious task because they do not yield to statistical methods easily.
Therefore proper organisation and presentation of such data is needed before any systematic statistical analysis is undertaken. Hence after collecting data the next step is to organise and present them in a classified form. Suppose you want to know the performance of students in mathematics and you have collected data on marks in mathematics of 100 students of your school. If you present them as a table, they may appear something like.
CLASSIFICATION OF DATA
The groups or classes of a classification is done in various ways. Instead of classifying your books according to subjects — “History”, “Geography”, “Mathematics”, “Science”, etc. — you could have classified them author-wise in an alphabetical order. Or, you could have also classified them according to the year of publication.
The way you want to classify them would depend on your requirement. Likewise the raw data is classified in various ways depending on the purpose. They can be grouped according to time. Such a classification is known as a Chronological Classification.
In such a classification, data are classified either in ascending or in descending order with reference to time such as years, quarters, months, weeks, etc. The following example shows the population of India classified in terms of years. The variable ‘population’ is a Time Series as it depicts a series of values for different years.
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NCERT Solutions Class 11 Statistics Chapter 3 Organisation of Data
Can there be any advantage in classifying things? Explain with an example from your daily life.
Classification refers to arranging or organising similar things into groups or classes. Classification of objects or things saves our valuable time and effort. Classification is done to group things in such a way that each group consists of similar items, e.g., we classify our wardrobe into different types of clothes or dresses according to the occasions on which they are to be worn. We put party wears, school uniform, casual daily wears and night wears separately. This helps us in an orderly arrangement of clothes and we can easily fetch the clothes we want at a particular time without searching through the whole wardrobe. Thus, it is evident that classification saves time and labour and helps to produce the desired results.
Explain the ‘exclusive’ and ‘inclusive’ methods used in classification of data.
Exclusive Method In this method, the classes are formed in such a way that the upper class limit of one class becomes the lower class limit of the next class. Continuity of the data is maintained in this method. Under this method, the upper class limit is excluded but the lower class limit of a class is included in the interval.
According to this method, an observation that is exactly equal to the upper class limit would not be included in that class but would be included in the next class. On the other hand, if it were equal to the lower class limit then it would be included in that class, e.g., if the class intervals are 0-5, 5-10, 15¬20 and so on, a value of 10 would be included in the 10-15 and not in the interval 5-10. Inclusive Method The inclusive method does not exclude the upper class limit in a class interval. It inlcludes the upper class in a class. Thus, both class limits are parts of the class interval, e.g., the class intervals of 0-5, 6-10, 11-15, and so on are inclusive.
NCERT Class 11 Statistics Textbook Chapter 3 With Answer PDF Free Download