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Class 11 Economics Short Questions with Answers: Correlation - 1

Q.1. Define correlation.
Ans.
Correlation is a statistical measure that shows the degree to which two or more variables fluctuate in relation to one another.

Q.2. How many types of correlation are there?
Ans.
Correlation is mainly classified into two types - positive correlation and negative correlation.

Q.3. What happens when there is a negative correlation between variables X and Y?
Ans. 
When there is negative correlation between variables X and Y then as X increases, Y decreases or as X decreases, Y increases. In simple terms, negative correlation between variables X and Y implies that variables move in opposite direction.

Q.4. Give an example of positive correlation.
Ans. 
Example of positive correlation: temperature and sale of cold drinks

Q.5. List the various techniques of measuring correlation.
Ans. 
The various techniques of measuring correlation
(i) Scatter diagram
(ii) Karl Pearson’s Coefficient of Correlation
(iii) Spearman’s Rank Correlation

Q.6. Explain the types of correlation.
Ans. 
Correlation is mainly classified into two types - positive correlation and negative correlation.
(i) Positive Correlation: In positive correlation, two variables move in the same direction, that is, when one increases, the other also increases and when one decreases, the other also decreases.
(ii) Negative Correlation: In negative correlation, two variables move in the opposite direction, that is, when one increases, the other decreases and when one decreases, the other increases.

Q.7. Discuss the importance of correlation.
Ans. 
Importance of correlation:
(i) Formation and Testing of Economic Laws: Correlation helps to study the relationship between various economic variables and hence, test the economic laws and principles. For example, the law of demand explains that when price of commodity increases, demand decreases and if price decreases, demand increases.
(ii) Studying Economic Problem: Correlation can be used to find out the cause behind an economic problem by explaining the reasons that are associated with the problem. For example, does price increase or decrease with rise is inflation. This problem can be tested with the help of correlation.
(iii) Formation of Policy: With the help of results derived from correlation, national policies can be formulated to deal with economic problems. For example, correlation can find out the reason behind the bounce in the prices. The government can formulate policies accordingly to curb price rise.

Q.8. What is scatter diagram?
Ans. 
Scatter diagram graphically shows the direction and degree of correlation between variables.

Q.9. What is the line of best fit?
Ans. 
The line of best fit is the one that passes through the scattered points such that it represents most of their points.

Q.10. State one shortcoming of scatter diagram.
Ans. 
Scatter diagram does not measure the precise extent of correlation.

Q.11. What type of correlations exists between variables if points lie very close to the line of best fit in an upward direction?
Ans. 
If points lie very close to the line of best fit in an upward direction, there exists high positive linear correlation between the variables.

Q.12. State the merits of scatter diagram.
Ans. 
The merits of scatter diagram are:
(i) It is a very simple method of studying correlation between two variables.
(ii) It indicates the relation between variables by giving just a glance.
(iii) This method is not affected by extreme values in the data.

Q.13. What are the demerits of scatter diagram?
Ans. 
The demerits of scatter diagram are:
(i) A scatter diagram does not measure the precise extent of correlation.
(ii) It is not a quantitative measure of the relationship between the variables.
(iii) The relationship between more than two variables cannot be shown using scatter diagram.

Q.14. Define Karl Pearson’s coefficient of correlation.
Ans. 
Karl Pearson’s coefficient of correlation gives the numerical value of the degree of correlation between two variables.

Q.15. State any one property of correlation coefficient.
Ans. 
Correlation coefficient (r) does not have a unit, that is, it is a pure number.

The document Class 11 Economics Short Questions with Answers: Correlation - 1 is a part of the Commerce Course Economics Class 11.
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FAQs on Class 11 Economics Short Questions with Answers: Correlation - 1

1. What is correlation?
Ans. Correlation is a statistical measure that depicts the relationship between two variables. It determines how changes in one variable are associated with changes in another variable. Correlation can be positive (both variables increase or decrease together), negative (one variable increases while the other decreases), or zero (no relationship).
2. How is correlation calculated?
Ans. Correlation is calculated using the correlation coefficient, also known as Pearson's correlation coefficient. It ranges from -1 to +1, where -1 represents a perfect negative correlation, +1 represents a perfect positive correlation, and 0 represents no correlation. The formula for calculating the correlation coefficient involves the covariance of the two variables and the standard deviations of each variable.
3. What does a correlation of 0.5 mean?
Ans. A correlation coefficient of 0.5 indicates a moderate positive correlation between the two variables. This means that there is a tendency for the variables to increase or decrease together, but the relationship is not extremely strong. It suggests that about 25% of the variability in one variable can be explained by the other variable.
4. Can correlation imply causation?
Ans. No, correlation does not imply causation. Correlation only shows the statistical relationship between two variables, but it does not prove that changes in one variable cause changes in the other. There might be other underlying factors or coincidences that contribute to the observed correlation. To establish causation, additional evidence and experimental research are required.
5. How can we interpret a correlation coefficient of -0.8?
Ans. A correlation coefficient of -0.8 represents a strong negative correlation between the two variables. This means that as one variable increases, the other variable tends to decrease, and vice versa. The relationship is highly predictable, suggesting that about 64% of the variability in one variable can be explained by the other variable.
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