Class 11 Economics - MAHARASHTRA
Correlation
The chapter 'Correlation' in Class 11 Economics under the Maharashtra State Board (MSBSHSE) introduces students to the statistical study of the relationship between two variables. You will learn how to measure the direction and degree of covariation between variables like price and demand, or income and consumption. The chapter covers types of correlation such as positive, negative, linear, and non-linear, alongside mathematical methods like Karl Pearson's coefficient of correlation and Spearman's rank correlation. This topic is highly scoring in board exams and forms the foundation for data analysis in higher economic studies.
Start Learning FreeKey Concepts
Correlation
A statistical measure that expresses the extent to which two variables are linearly related, indicating how changes in one variable are associated with changes in another.
Positive Correlation
A relationship where two variables move in the same direction; when one variable increases, the other also increases, and vice versa.
Negative Correlation
An inverse relationship where two variables move in opposite directions; as one variable increases, the other decreases.
Karl Pearson's Coefficient of Correlation
A mathematical method used to measure the exact numerical degree of linear relationship between two quantitative variables, denoted by 'r'.
Spearman's Rank Correlation
A non-parametric method used to find the correlation between qualitative variables or ranks assigned to data, denoted by 'R'.
Important Formulas
Board Exam Info
In the Maharashtra (MSBSHSE) Class 11 Economics board exams, this chapter typically carries around 8 to 10 marks. Common question types include objective questions (MCQs, match the following), short answer questions defining types of correlation, and practical numerical problems on calculating Karl Pearson's or Spearman's rank correlation coefficients.
Frequently Asked Questions
What is the difference between correlation and causation?
Correlation simply means two variables move together, but it does not prove that one variable causes the change in the other. Causation implies a direct cause-and-effect relationship.
What is the range of values for Karl Pearson's correlation coefficient?
The value of 'r' always lies between -1 and +1. A value of +1 means perfect positive correlation, -1 means perfect negative correlation, and 0 means no correlation.
When should we use Spearman's rank correlation instead of Karl Pearson's method?
Spearman's rank correlation is used when data is qualitative (based on beauty, honesty, or ranks) or when extreme values might distort the Pearson coefficient.
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