SUMMARY: The chapter "Organisation of Data" in Class 11 Economics focuses on the systematic arrangement and presentation of data for analysis and interpretation in statistics.
KEY TOPICS: data classification, frequency distribution, tabulation, types of data, qualitative and quantitative data, discrete and continuous data, cumulative frequency distribution, graphical representation of data, bar diagrams, pie charts
A variable that takes only whole-number values is classified as:
In the exclusive method of classification, which of the following is true?
The difference between the upper and lower class limits is called:
The average of the upper and lower class limits is the:
Which of the following is an example of qualitative classification?
Which of the following best describes 'classification of data'?
Data that can take any value within a given range is called:
The number of students scoring marks in the range 40–50 in a class test is an example of:
In a frequency distribution, the class interval 20–30 has a lower class limit of:
Which of the following is an example of qualitative (or categorical) data?
Cumulative frequency of a class interval is obtained by:
A frequency distribution in which class intervals do not overlap and each observation belongs to exactly one class is called:
If the class intervals are 0–10, 10–20, 20–30, the mid-value (class mark) of the class 10–20 is:
In a 'less than' cumulative frequency distribution, the cumulative frequency against the class 0–10 in the following data is: Class: 0–10 (f=5), 10–20 (f=8), 20–30 (f=12). What is the cumulative frequency for 'less than 20'?
A frequency distribution table shows the following: Class 10–20 has frequency 6, class 20–30 has frequency 10, class 30–40 has frequency 4. The relative frequency of the class 20–30 is:
Define classification of data.
Distinguish between discrete and continuous variables.
Distinguish between the inclusive and exclusive methods of class intervals.
What is a frequency array?
State any two principles of constructing a frequency distribution.
What is meant by classification of data in statistics?
Distinguish between qualitative and quantitative data with one example each.
What is a frequency distribution table? Why is it useful?
Differentiate between discrete and continuous data with suitable examples.
What is meant by class interval and class frequency in a frequency distribution?
Explain the objectives of classification of data.
Explain different types of classification of data with examples.
Describe the procedure of constructing a frequency distribution for raw continuous data.
Distinguish between exclusive and inclusive methods of class intervals with examples.
Explain the concept of a statistical series and its types.
Compare classification and tabulation of data with the help of a table.
Assertion (A): Classification of raw data helps in revealing patterns.
Reason (R): Grouping similar items together makes the characteristics of the data visible.
Assertion (A): A continuous variable can take any value within an interval.
Reason (R): Unlike discrete variables it is not restricted to isolated numbers and can take fractional values.
Assertion (A): The exclusive method avoids ambiguity at class boundaries.
Reason (R): The upper limit of a class is excluded from that class and becomes the lower limit of the next.
Assertion (A): Too many class intervals reduce the clarity of a frequency distribution.
Reason (R): Extra classes spread the observations thin and hide the pattern that a moderate number would reveal.
Assertion (A): A frequency distribution can only be prepared for discrete data.
Reason (R): Frequency distributions can also be built for continuous variables by grouping values into class intervals.
Assertion (A): Qualitative data cannot be measured numerically.
Reason (R): Qualitative data describes attributes or characteristics such as gender, colour, or religion which are non-numeric in nature.
Assertion (A): A frequency distribution table helps in summarising a large set of raw data.
Reason (R): Frequency distribution arranges data into classes and shows how frequently each class occurs, making data easier to analyse.
Assertion (A): Discrete data can take any value within a given range.
Reason (R): Continuous data can take any value within a range, whereas discrete data can only take specific, countable values.
Statement 1: Qualitative classification uses non-numerical attributes.
Statement 2: Quantitative classification uses numerical variables.
Statement 1: The difference between the upper and lower limits of a class is the class width.
Statement 2: The average of the upper and lower limits of a class is the class mid-point.
Statement 1: The class mid-point is used to represent a class for averaging.
Statement 2: The mid-point is the arithmetic mean of the upper and lower class limits.
Statement 1: The inclusive method of class intervals may leave apparent gaps between successive classes.
Statement 2: The data must therefore be adjusted before drawing a histogram or an ogive.
Statement 1: Raw data is unorganised and difficult to analyse.
Statement 2: Classified or grouped data is arranged so that summary statistics can be computed.
Statement 1: Qualitative data refers to data that can be measured numerically.
Statement 2: Quantitative data refers to data that can be expressed in numerical terms.
Statement 1: A frequency distribution table shows how data is distributed across different classes or intervals.
Statement 2: Cumulative frequency is obtained by adding the frequency of each class to the sum of frequencies of all preceding classes.
Statement 1: Discrete data can take any value within a given range, including fractions and decimals.
Statement 2: Continuous data can take any value within a given range, including fractions and decimals.
Study the frequency distribution of marks and answer:
| Marks | Frequency |
|---|---|
| 0-10 | 4 |
| 10-20 | 8 |
| 20-30 | 12 |
| 30-40 | 10 |
| 40-50 | 6 |
Study the qualitative and quantitative classification and answer:
| Basis | Type | Example |
|---|---|---|
| Sex | Qualitative | Male / Female |
| Literacy | Qualitative | Literate / Illiterate |
| Age | Quantitative (continuous) | 0-10, 10-20, ... years |
| Family size | Quantitative (discrete) | 1, 2, 3, ... members |
Construct a frequency distribution with a class width of 10 for the following marks of 30 students, using the exclusive method.
| Marks (raw) |
|---|
| 5, 8, 9, 12, 14, 15, 16, 18, 18, 19 |
| 21, 22, 24, 25, 25, 26, 27, 28, 29, 29 |
| 31, 32, 34, 35, 37, 38, 39, 41, 44, 48 |
Using the less-than cumulative method, compute the cumulative frequencies and state the median class.
| Class | Frequency |
|---|---|
| 0-10 | 4 |
| 10-20 | 6 |
| 20-30 | 12 |
| 30-40 | 10 |
| 40-50 | 8 |
Study the frequency histogram of student marks and answer:
Based on the given diagram, answer the following:
Based on the given bar chart showing the frequency distribution of marks obtained by 50 students, answer the following:
Based on the given pie chart showing the distribution of household expenditure, answer the following:
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