CBSE Class 12 Geography Chapter 2: Data Processing NCERT Solutions

Q: What is the main focus of Chapter 2: Data Processing in Class 12 Geography?

Chapter 2 focuses on fundamental statistical concepts used in data analysis, including measures of central tendency (mean, median, mode), correlation, and dispersion, which are essential for interpreting geographical data.

Q: Which measure of central tendency is best when dealing with extreme values?

The median is the best measure of central tendency when dealing with extreme values because it is not affected by outliers. The mode is also unaffected by extreme values.

Q: How can we visually represent correlation?

Correlation can be visually represented using a scatter plot. The pattern of the plotted points indicates the type and strength of the correlation between two variables.

Q: What is the difference between perfect positive and perfect negative correlation?

Perfect positive correlation means variables increase or decrease together proportionally (e.g., doubling one doubles the other). Perfect negative correlation means as one variable increases, the other decreases proportionally (e.g., doubling one halves the other).

Q: Why is dispersion important in data analysis?

Dispersion measures the spread or variability of data points around the central tendency. It provides a more complete picture of the data's distribution than central tendency alone.

Q: How do the mean, median, and mode relate in a normal distribution?

In a perfectly normal distribution, the mean, median, and mode all coincide at the center, representing the peak of the distribution.

Reviewed by NCERT Help Editorial Team · Updated on 29 Jul 2026

NCERT Solutions PDF Class 12 PDF

This chapter, "Data Processing" for CBSE Class 12 Geography, provides essential NCERT Solutions. It covers key statistical concepts like measures of central tendency (mean, median, mode), understanding their properties and applications. Students will learn about correlation, including scatter plots and different types like positive, negative, and perfect correlation, as well as the concept of dispersion and its importance in data analysis. The solutions explain how these measures help in interpreting geographical data effectively. This resource is designed to help students grasp these fundamental statistical tools, clarify doubts, and prepare thoroughly for their examinations by offering clear explanations and structured answers.

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Quick info

Board	CBSE
Class	Class 12
Subject	Geography Practical Work in Geography
Session	2026
Language	English
Type	NCERT Solutions
Chapter	Chapter 2

Chapter summary

Chapter 2 of the Class 12 Geography Practical Work focuses on Data Processing. It introduces students to fundamental statistical concepts crucial for analyzing geographical data. The solutions cover measures of central tendency (mean, median, mode), their definitions, advantages, and relative positions in different distributions. It also delves into correlation, explaining scatter plots and the concept of perfect correlation, and defines dispersion as a measure of data spread. This chapter equips students with the basic analytical skills needed for practical geography.

Learning outcomes

Understand the definitions and properties of mean, median, and mode.
Identify the measure of central tendency unaffected by extreme values.
Explain the concept of correlation and interpret scatter plots.
Define and differentiate between positive, negative, and perfect correlation.
Understand the concept of dispersion and its relation to central tendency.

Topics covered

Paper topics

Measures of Central Tendency
Mean
Median
Mode
Correlation
Scatter Plot
Positive Correlation
Negative Correlation
Perfect Correlation
Dispersion
Normal Distribution
Skewed Distribution

Important topics

Measures of Central Tendency (Mean, Median, Mode)
Properties of Median and Mode
Interpreting Scatter Plots
Types of Correlation (Positive, Negative, Perfect)
Concept of Dispersion

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Questions and Solutions

Multiple Choice Questions

(i). Choose the right answer from the four alternatives given below: The measure of central tendency that does not get affected by extreme values

Mean
Mean and mode
Mode
Median

Solution: The correct answer is (d) Median. The median is the middle value in a dataset when arranged in order. Extreme values (very large or very small) at the ends of the dataset do not influence the position of the middle value, thus the median is unaffected by them. While the mode is also generally unaffected by extreme values, the median is the more robust measure in this context.

(ii). The measure of central tendency always coinciding with the hump of any distribution is:

Median
Median and Mode
Mean
Mode

Solution: The correct answer is (b) Median and Mode. The 'hump' of a distribution represents the most frequent values. The mode is defined as the value with the highest frequency, so it always coincides with the peak. In many common distributions, including the normal distribution, the median (the middle value) also aligns with the peak and the mean.

(iii). A scatter plot represents negative correlation if the plotted values run from:

Upper left to lower right
Lower left to upper right
Left to right
Upper right to lower left

Solution: The correct answer is (a) Upper left to lower right. When data points on a scatter plot trend downwards from the top-left corner to the bottom-right corner, it indicates that as the values of one variable increase, the values of the other variable tend to decrease. This inverse relationship is characteristic of negative correlation.

Short Answer Questions (approx. 30 words)

(i). Define the mean.

Solution: The mean is a measure of central tendency calculated by summing all the values in a dataset and then dividing the sum by the total number of observations. It represents the arithmetic average of the data.

$\overline{X} = \frac{\text{Sum of observations}}{\text{No. of observations}}$

(ii). What are the advantages of using mode?

Solution: The mode is the value that appears most frequently in a dataset. Its primary advantages are that it is easily understood, can be determined for categorical data, is not affected by extreme values, and can be calculated even for open-ended frequency distributions where the mean or median might be undefined.

(iii). What is dispersion?

Solution: Dispersion refers to the extent to which a set of data points are spread out or scattered around a measure of central tendency (like the mean or median). It quantifies the variability within a dataset, indicating how much individual values differ from the average.

(iv). Define correlation.

Solution: Correlation is a statistical measure that describes the strength and direction of a linear relationship between two or more variables. It indicates whether and how strongly pairs of variables tend to move together.

(v). What is perfect correlation?

Solution: Perfect correlation exists when there is a precise proportional relationship between two variables. Perfect positive correlation occurs when both variables increase or decrease together by the same proportion (e.g., doubling one variable also doubles the other). Perfect negative correlation occurs when one variable increases as the other decreases by the same proportion (e.g., doubling one variable halves the other).

(vi). What is the maximum extent of correlation?

Solution: The extent of correlation is measured by the correlation coefficient, typically denoted by 'r'. Its value ranges from -1 to +1. A value of +1 indicates perfect positive correlation, -1 indicates perfect negative correlation, and 0 indicates no linear correlation. Values closer to ±1 signify a stronger correlation, while values closer to 0 indicate a weaker correlation.

$-1 \le r \le +1$

Long Answer Questions (approx. 125 words)

(i). Explain relative positions of mean, median and mode in a normal distribution and skewed distribution with the help of diagrams.

Solution:

Normal Distribution: In a perfectly symmetrical normal distribution, the mean, median, and mode are all equal and located at the center of the distribution, which is also the highest point (the 'hump') of the bell-shaped curve. The data is evenly spread around this central point.

Skewed Distribution: In skewed distributions, the mean, median, and mode are not equal.

Positively Skewed (Right Skewed): The tail of the distribution extends to the right. The mode is at the peak, the median is to the right of the mode, and the mean is pulled furthest to the right by the extreme high values. The order is: Mode < Median < Mean.
Negatively Skewed (Left Skewed): The tail of the distribution extends to the left. The mode is at the peak, the mean is pulled furthest to the left by the extreme low values, and the median lies between them. The order is: Mean < Median < Mode.

Diagrams would visually represent these positions on a curve, showing the peak for the mode, the middle point for the median, and the average position for the mean in each type of distribution.

Common mistakes

Confusing the properties of mean, median, and mode, especially regarding extreme values.
Misinterpreting scatter plots and the direction of correlation.
Not clearly distinguishing between perfect positive and perfect negative correlation.
Confusing correlation with causation.

Revision tips

Focus on the definitions and unique properties of mean, median, and mode.
Memorize the conditions for positive, negative, and perfect correlation.
Understand the visual representation of correlation through scatter plots.
Review the relationship between central tendency and dispersion.

Practice MCQs

Q1. Which measure of central tendency is least affected by extreme values in a dataset?

Q2. In a normal distribution, where does the mode typically coincide?

Q3. A scatter plot showing data points trending from the upper left to the lower right indicates:

Q4. What does perfect positive correlation imply?

Q5. The range of possible values for a correlation coefficient (r) is:

Frequently asked questions

What is the main focus of Chapter 2: Data Processing in Class 12 Geography?