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The assumption taken by Karl Pearson for correlation coefficient is-
A) The Two Variables
Are Linearly Correlated
B) There Is A Cause And
Effect Relationship
Between The Variables
C) A & B Both D) None?
A) The Two Variables
Are Linearly Correlated
B) There Is A Cause And
Effect Relationship
Between The Variables
C) A & B Both D) None?
Most Upvoted Answer
The assumption taken by Karl Pearson for correlation coefficient is- A...
Assumption for Correlation Coefficient by Karl Pearson
Assumption: The Two Variables Are Linearly Correlated
- Karl Pearson's correlation coefficient assumes that the relationship between the two variables is linear. This means that the relationship between the variables can be described by a straight line.
- The correlation coefficient measures the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where -1 indicates a perfect negative linear relationship, 0 indicates no linear relationship, and 1 indicates a perfect positive linear relationship.
Explanation:
- Pearson's correlation coefficient is specifically designed to measure the linear relationship between two variables. It does not consider non-linear relationships.
- If the relationship between the variables is non-linear, the correlation coefficient may not accurately reflect the strength and direction of the relationship.
- Therefore, it is important to assess the linearity of the relationship before using Pearson's correlation coefficient to measure the association between two variables.
In conclusion, Karl Pearson's assumption for correlation coefficient is that the two variables are linearly correlated. This assumption is crucial for accurately interpreting the results of the correlation coefficient analysis.
Assumption: The Two Variables Are Linearly Correlated
- Karl Pearson's correlation coefficient assumes that the relationship between the two variables is linear. This means that the relationship between the variables can be described by a straight line.
- The correlation coefficient measures the strength and direction of the linear relationship between two variables. It ranges from -1 to 1, where -1 indicates a perfect negative linear relationship, 0 indicates no linear relationship, and 1 indicates a perfect positive linear relationship.
Explanation:
- Pearson's correlation coefficient is specifically designed to measure the linear relationship between two variables. It does not consider non-linear relationships.
- If the relationship between the variables is non-linear, the correlation coefficient may not accurately reflect the strength and direction of the relationship.
- Therefore, it is important to assess the linearity of the relationship before using Pearson's correlation coefficient to measure the association between two variables.
In conclusion, Karl Pearson's assumption for correlation coefficient is that the two variables are linearly correlated. This assumption is crucial for accurately interpreting the results of the correlation coefficient analysis.
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The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None?
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The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None? for UPSC 2024 is part of UPSC preparation. The Question and answers have been prepared according to the UPSC exam syllabus. Information about The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None? covers all topics & solutions for UPSC 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None?.
The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None? for UPSC 2024 is part of UPSC preparation. The Question and answers have been prepared according to the UPSC exam syllabus. Information about The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None? covers all topics & solutions for UPSC 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for The assumption taken by Karl Pearson for correlation coefficient is- A) The Two Variables Are Linearly Correlated B) There Is A Cause And Effect Relationship Between The Variables C) A & B Both D) None?.
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