Class 11 Economics - GUJARAT
Correlation
The chapter 'Correlation' in Class 11 Economics introduces students to the statistical measurement of the relationship between two variables. Under the GSEB curriculum, students learn how changes in one economic variable, like price, affect another, like demand. The chapter covers types of correlation such as positive, negative, linear, and non-linear, alongside practical methods of measurement including Karl Pearson's coefficient of correlation and Spearman's rank correlation. Mastering this chapter is crucial for board exams as it carries significant weight in numerical problems and graphical representation, forming the foundation for advanced economic analysis in higher grades.
Start Learning FreeKey Concepts
Correlation
A statistical measure that expresses the extent to which two variables are linearly related to each other.
Positive Correlation
A relationship where two variables move in the same direction, meaning if one increases, the other also increases.
Negative Correlation
A relationship where two variables move in opposite directions, meaning if one 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 variables, denoted by 'r'.
Spearman's Rank Correlation
A non-parametric method used to measure correlation based on the ranks of the data rather than their actual numerical values.
Important Formulas
Board Exam Info
In the Gujarat (GSEB) Class 11 Economics board exams, this chapter typically carries around 8 to 10 marks. Common question types include short objective questions, definitions of correlation types, and long numerical problems based on Karl Pearson's and Spearman's rank formulas.
Frequently Asked Questions
What is the range of the correlation coefficient (r)?
The value of the correlation coefficient always lies between -1 and +1 inclusive.
When should we use Spearman's rank correlation instead of Karl Pearson's method?
Spearman's rank correlation is used when data is qualitative or based on subjective assessment like beauty, honesty, or ranks, rather than exact quantitative measurements.
Does high correlation mean causation between two variables?
No, correlation only shows that two variables are related, but it does not prove that changes in one variable cause changes in the other.
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