NCERT Notes for Class 11 statistics Chapter 3 Organisation of data

Class 11 statistics Chapter 3 Organisation of data

NCERT Notes for Class 11 statistics Chapter 3 Organisation of data, (Statistics) exam are Students are taught thru NCERT books in some of state board and CBSE Schools.  As the chapter involves an end, there is an exercise provided to assist students prepare for evaluation.  Students need to clear up those exercises very well because the questions withinside the very last asked from those. 

Sometimes, students get stuck withinside the exercises and are not able to clear up all of the questions.  To assist students, solve all of the questions and maintain their studies without a doubt, we have provided step by step NCERT Notes for the students for all classes.  These answers will similarly help students in scoring better marks with the assist of properly illustrated Notes as a way to similarly assist the students and answering the questions right.

NCERT Notes for Class 11 statistics Chapter 3 Organisation of data

Class 11 statistics Chapter 3 Organisation of data


The data collected from primary and secondary sources are raw or unclassified. Once the data are collected, the next step is to classify them for further statistical analysis. Classification brings order in the data

  • Classification, is arranging or organising things into groups or classes based on some criteria.
  • The unclassified data is called is called raw data.
  • In Chronological classification data are classified either in ascending or in descending order with reference to time such as years, quarters, months, weeks, etc.
  • In Spatial Classification the data are classified with reference to geographical locations such as countries, states, cities, districts, etc.
  • Some attributes for example, nationality, literacy, religion, gender, marital status, etc. cannot be measured. Classification of such attributes is called Qualitative Classification.
  • Some attributes for example, height, weight, age, income, marks of students, etc., are quantitative in nature. Classification of such attributes is called Quantitative Classification.


Variables differ on the basis of specific criterion.

They are broadly classified into two types:

  1. Continuous
  2. Discrete.
  • A continuous variable can take any numerical value. It may take integral values (1, 2, 3, 4, …), fractional values (1/2, 2/3, 3/4, …), and values that are not exact fractions.(eg. height, weight, mark etc)
  • A discrete variable can take only certain values. Its value changes only by finite “jumps”.(eg. Number of children in a family, number of books in a library etc.


  • A frequency distribution is a comprehensive way to classify raw data of a quantitative variable.
  • It shows how different values of a variable are distributed in different classes along with their corresponding class frequencies.
  • Each class in a frequency distribution table is bounded by Class Limits. Class limits are the two ends of a class.
  • The lowest value is called the Lower-Class Limit and the highest value the Upper-Class Limit.
  • The Class Mid-Point or Class Mark is the middle value of a class. It lies halfway between the lower-class limit and the upper-class limit of a class.
  • Class Mid-Point or Class Mark = (Upper Class Limit + Lower Class Limit)/2
  • Frequency Curve is a graphic representation of a frequency distribution.
  • Class intervals are of two types:

(i) Inclusive class intervals: In this case, values equal to the lower and upper limits of a class are included in the frequency of that same class.

(ii) Exclusive class intervals: In this case, an item equal to either the upper or the lower class limit is excluded from the frequency of that class.

  • In the case of discrete variables, both exclusive and inclusive class intervals can be used.
  • Frequency of an observation means how many times that observation occurs in the raw data.


  • A Bivariate Frequency Distribution can be defined as the frequency distribution of two variables.

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