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Exercises · Q7

Q.What is 'loss of information' in classified data?

Telangana TsbieTextbookSubjective· 2mImportance★★★★★est
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Classifying data into classes is useful, but it comes at a cost: the exact value of each observation disappears once it is put into a class. This is the 'loss of information' — every item in a class is thereafter assumed to equal the class midpoint.

What it means

Grouping raw data into class intervals summarises them neatly, but in the process the individual values are lost. Once an observation is placed in a class, we only know which class it belongs to, not its exact figure.

Why the information is lost

When we later calculate statistics on grouped data, we assume that every observation in a class is equal to the midpoint of that class.

  • Suppose a class 30–40 contains the values 31, 34, 37 and 39.
  • In the classified table these appear only as "four items in class 30–40".
  • For calculation each is taken to be the midpoint 35 — so the real figures 31, 34, 37, 39 are no longer available. …

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