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NCERT Solutions For Class 11 Statistics for Economics Chapter 3 Organisation of Data
Ncert solutions for class 11 Statistics for Economics Chapter 3 Organisation of Data are prepared by CBSE student eCARE expert to score good marks in class 11. Classes 11 Statistics for Economics Chapter 3 Organisation of Data contain many topics which are very important to score good in class 11. There are some important topic mentioned below:
Statistics is a part of mathematics that deals with the gathering, formation, analysis, elucidation, and presentation of data.
NCERT Solution For Class 11 Commerce Statistics Chapter 3 – Organisation Of Data furnishes us with an all-inclusive data to all the concepts. As the students would have to learn the basic fundamentals about the subject of statistics in Class 11, this curriculum for Class 11 is a comprehensive study material; which explains the concepts in a great way.
Concepts covered in this chapter –
- Introduction
- Raw Data
- Classification of data
- Variables: Continuous and discrete
- What is a frequency distribution?
- How to prepare a Frequency Distribution?
- Should we have equal or unequal sized class intervals?
- How many classes should we have?
- How should we determine the class limits?
- What should be the size of each class?
- Adjustment in Class Interval
- How should we get the frequency for each class?
- Loss of Information
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Some questions are asked by class 11 students related to Statistics for Economics
Question 1.
Which of the following alternatives is true?
(i) The class mid-point is equal to
(a) the average of the upper class limit and the lower class limit
(b) the product of upper class limit and the lower class limit
(c) the ratio of the upper class limit and the lower class limit
(d) None of the above
Answer:
(a) The class mid-point is the middle value of a class. It lies halfway between the lower class limit and the upper class limit of a class and is calculated as
Class Mid-Point or Class Mark = (Upper Class Limit + Lower Class Limit) 2
(ii) The frequency distribution of two variables is known as
(a) Univariate Distribution
(b) Bivariate Distribution
(c) Multivariate Distribution
(d) None of the above
Answer:
(b) Bi means two and hence the frequency distribution of two variables is known as Bivariate Distribution.
(iii) Statistical calculation in classified data are based on
(a) the actual values of observations
(b) the upper class limits
(c) the lower class limits
(d) the class mid-points
Answer:
(d) The class mid-points of each class is used to represent the class and therefore, it is used in further calculations after the raw data are grouped into classes.
(iv) Under exclusive method,
(a) the upper class limit of a class is excluded in the class interval
(b) the upper class limit of a class is included in the class interval
(c) the lower class limit of a class is excluded in the class interval
(d) the lower class limit of a class is included in the class interval
Answer:
(a) Under the exclusive method we form classes in such a way that the lower limit of a class coincides with the upper class limit of the previous class. Under the method, the upper class limit is excluded but the lower class limit of a class is included in the interval.
(v) Range is the
(a) difference between the largest and the smallest observations
(b) difference between the smallest and the largest observations
(c) average of the largest and the smallest observations
(d) ratio of the largest to the smallest observation
Answer:
(a) The variation in variable’s value are captured by its range. The range is the difference between the largest and the smallest values of the variable. A large range indicates that the values of the variable are widely spead.
Question 2.
Can there be any advantage in classifying things? Explain with an example from your daily life.
Answer:
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.
Question 3.
What is a variable? Distinguish between a discrete and a continuous variable.
Answer:
A measurable characteristic which takes different values at different points of time and in different circumstance is called a variable as it keeps varying. Different varibles vary differently and depending on the way they vary, they are broadly classified into two types
| S.N. | Discrete Variable | Continuous Variable |
| (i) | A discrete variable can take only whole numbers. | A continuous variable can take any numerical value. |
| (ii) | Discrete varibles increase in finite jumps from one value to another and cannot take any intermediate value between them. | Continuous variables can take any conceivable value and can be broken into infinite gradations. |
| (iii) | Examples-number of workers in a factory, number of residents in a colony, etc. | Examples-height, weight, distance, etc. |
Question 4.
Explain the ‘exclusive’ and ‘inclusive’ methods used in classification of data.
Answer:
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.