NCERT Class 11 Economics Statistics for Economics: Chapter 6 — Correlation
This chapter introduces the concept of correlation in statistics, focusing on understanding the relationship between two variables. It explains that correlation analysis systematically examines such relationships, distinguishing them from mere coincidence or causation. The chapter highlights that correlation measures the direction and intensity of a relationship, not the cause and effect. It discusses how changes in one variable might be associated with changes in another, whether they move in the same or opposite directions. Examples like the relationship between temperature and ice-cream sales, or supply and price of tomatoes, are used to illustrate these concepts. The chapter also warns against misinterpreting correlation as causation, citing examples where a third variable influences the observed relationship. It aims to equip students with the ability to analyze the degree and direction of relationships between variables, a crucial skill in statistical analysis for CBSE students.
Quick info
| Board | CBSE / NCERT |
|---|---|
| Class | Class 11 |
| Subject | Economics |
| Book | Statistics for Economics |
| Chapter | Chapter 6 — Correlation |
| Language | English |
| PDF type | NCERT Textbook |
| Session | CBSE 2026 |
| Reading time | 3 minutes |
| Word count | 542 |
Learning outcomes
- Understand the meaning of correlation.
- Understand the nature of relationship between two variables.
- Calculate different measures of correlation.
- Analyze the degree and direction of relationships.
Vocabulary
| Word | Meaning |
|---|---|
| Correlation | A statistical measure examining the relationship between two variables. |
| Variables | Quantities that can change or vary. |
| Causation | The relationship where one event is the direct result of another. |
| Coincidence | A relationship that occurs by chance without a causal link. |
| Covariation | The measure of how two variables change together. |
| Direction | The way in which variables change in relation to each other (e.g., same or opposite). |
| Intensity | The strength of the relationship between variables. |
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Practice questions
- What is the primary purpose of correlation analysis? Answer: To examine and measure the systematic relationship between two variables.
- Can correlation imply a cause-and-effect relationship? Answer: No, correlation measures covariation, not causation. It should never be interpreted as implying cause and effect.
- Give an example of a relationship that might be a coincidence. Answer: The relationship between the arrival of migratory birds and birth rates in a locality.
- What does it mean if two variables move in the same direction? Answer: It indicates a positive correlation, where an increase in one variable is associated with an increase in the other.
Frequently asked questions
What is correlation in statistics?
Correlation is a statistical method used to measure the strength and direction of the linear relationship between two variables.
Does correlation mean one variable causes another?
No, correlation indicates that two variables tend to move together, but it does not imply that one causes the other. This is known as the 'correlation does not imply causation' principle.
What are the types of relationships correlation can show?
Correlation can show positive relationships (variables move in the same direction) or negative relationships (variables move in opposite directions).
Can correlation be a coincidence?
Yes, sometimes a correlation between two variables might be purely coincidental and not due to any underlying causal link.
What is the role of a third variable in correlation?
A third, unobserved variable can sometimes influence two other variables, creating a correlation between them that is not directly causal.
What does 'intensity' of correlation refer to?
Intensity refers to how strong the relationship is between the two variables. A stronger intensity means the variables are more closely related.
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NCERT Class 11 Economics — Statistics for Economics — Chapter 6 — Correlation. Verified by NCERT Help Editorial Team. Reviewed on 29 Jul 2026. Last updated 10 Aug 2026.