Class 11 Economics - CBSE
Correlation
The chapter 'Correlation' in Class 11 CBSE Economics introduces students to the statistical tools used to measure the relationship between two variables. You will learn how changes in one variable, such as price, affect another, like demand. The chapter covers types of correlation—positive, negative, linear, and non-linear—along with practical methods of measurement including Karl Pearson's coefficient of correlation and Spearman's rank difference method. Mastering this chapter is crucial for your CBSE board exams as it carries significant weightage, frequently featuring both conceptual questions and numerical problems that test your data interpretation skills.
Start Learning FreeKey Concepts
Correlation
A statistical technique that describes and measures the degree of relationship between two variables.
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, so if one increases, the other decreases.
Karl Pearson's Coefficient of Correlation
A mathematical method that gives a precise numerical value (denoted by 'r') ranging from -1 to +1 to measure linear correlation.
Spearman's Rank Correlation
A non-parametric method used to find the correlation between qualitative variables or ranks based on attributes like beauty, honesty, or performance.
Important Formulas
Board Exam Info
In the CBSE Class 11 Economics exam, Correlation typically carries around 6 to 8 marks. Questions usually include a direct numerical problem on calculating Karl Pearson's or Spearman's rank correlation coefficient, alongside 1-mark conceptual MCQs or short-answer questions defining types of correlation.
Frequently Asked Questions
What does a correlation coefficient of zero mean?
A correlation of zero means there is no linear relationship between the two variables; they are completely independent of each other.
Can correlation prove cause and effect?
No, correlation only shows that two variables move together, but it does not prove that one variable causes the change in the other.
When should we use Spearman's rank method instead of Karl Pearson's?
Spearman's rank method is used when data involves qualitative characteristics (like ranking candidates based on honesty) or when extreme values might distort the Pearson coefficient.
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