CA Foundation Exam > CA Foundation Questions > For finding correlation between two attribute...
Start Learning for Free
For finding correlation between two attributes, we consider
- a)Pearson’s correlation coefficient
- b)Scatter diagram
- c)Spearman’s rank correlation coefficient
- d)Coefficient of concurrent deviations
Correct answer is option 'C'. Can you explain this answer?
| FREE This question is part of | Download PDF Attempt this Test |
Most Upvoted Answer
For finding correlation between two attributes, we considera)Pearson&#...
Explanation:
When we want to find the correlation between two attributes, we use statistical methods to quantify the relationship between those attributes. One such method is the Spearman's rank correlation coefficient.
Spearman's Rank Correlation Coefficient:
Spearman's rank correlation coefficient is a measure of the strength and direction of the relationship between two variables that are measured on an ordinal or interval scale. It measures the degree of association between two ranked variables. It is denoted by the symbol 'ρ' and ranges between -1 and +1.
Scatter Diagram:
A scatter diagram is a graph that shows the relationship between two variables. It is a visual representation of the correlation between two attributes. A scatter diagram can help us to identify the type of relationship between two attributes.
Pearson's Correlation Coefficient:
Pearson's correlation coefficient is a measure of the linear relationship between two variables. It measures the strength and direction of the relationship between two variables that are measured on an interval or ratio scale. Pearson's correlation coefficient is denoted by the symbol 'r' and ranges from -1 to +1.
Coefficient of Concurrent Deviations:
The coefficient of concurrent deviations is a measure of the degree of association between two variables. It is calculated by dividing the sum of the product of the deviations of the two variables from their respective means by the product of their standard deviations.
Conclusion:
All of the above methods are used for finding the correlation between two attributes. However, Spearman's rank correlation coefficient is the most appropriate method when the variables are measured on an ordinal or interval scale.
When we want to find the correlation between two attributes, we use statistical methods to quantify the relationship between those attributes. One such method is the Spearman's rank correlation coefficient.
Spearman's Rank Correlation Coefficient:
Spearman's rank correlation coefficient is a measure of the strength and direction of the relationship between two variables that are measured on an ordinal or interval scale. It measures the degree of association between two ranked variables. It is denoted by the symbol 'ρ' and ranges between -1 and +1.
Scatter Diagram:
A scatter diagram is a graph that shows the relationship between two variables. It is a visual representation of the correlation between two attributes. A scatter diagram can help us to identify the type of relationship between two attributes.
Pearson's Correlation Coefficient:
Pearson's correlation coefficient is a measure of the linear relationship between two variables. It measures the strength and direction of the relationship between two variables that are measured on an interval or ratio scale. Pearson's correlation coefficient is denoted by the symbol 'r' and ranges from -1 to +1.
Coefficient of Concurrent Deviations:
The coefficient of concurrent deviations is a measure of the degree of association between two variables. It is calculated by dividing the sum of the product of the deviations of the two variables from their respective means by the product of their standard deviations.
Conclusion:
All of the above methods are used for finding the correlation between two attributes. However, Spearman's rank correlation coefficient is the most appropriate method when the variables are measured on an ordinal or interval scale.
Free Test
FREE
| Start Free Test |
Community Answer
For finding correlation between two attributes, we considera)Pearson&#...
Attributes is also called as qualitative characteristics (i.e. which can't be measured).
so for finding correlation between two attributes , we consider spearman's rank correlation coefficient as it
Attention CA Foundation Students!
To make sure you are not studying endlessly, EduRev has designed CA Foundation study material, with Structured Courses, Videos, & Test Series. Plus get personalized analysis, doubt solving and improvement plans to achieve a great score in CA Foundation.
|
Explore Courses for CA Foundation exam
|
|
Similar CA Foundation Doubts
Top Courses for CA FoundationView all
For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer?
Question Description
For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? for CA Foundation 2024 is part of CA Foundation preparation. The Question and answers have been prepared according to the CA Foundation exam syllabus. Information about For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? covers all topics & solutions for CA Foundation 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer?.
For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? for CA Foundation 2024 is part of CA Foundation preparation. The Question and answers have been prepared according to the CA Foundation exam syllabus. Information about For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? covers all topics & solutions for CA Foundation 2024 Exam. Find important definitions, questions, meanings, examples, exercises and tests below for For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer?.
Solutions for For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? in English & in Hindi are available as part of our courses for CA Foundation.
Download more important topics, notes, lectures and mock test series for CA Foundation Exam by signing up for free.
Here you can find the meaning of For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? defined & explained in the simplest way possible. Besides giving the explanation of
For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer?, a detailed solution for For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? has been provided alongside types of For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? theory, EduRev gives you an
ample number of questions to practice For finding correlation between two attributes, we considera)Pearson’s correlation coefficientb)Scatter diagramc)Spearman’s rank correlation coefficientd)Coefficient of concurrent deviationsCorrect answer is option 'C'. Can you explain this answer? tests, examples and also practice CA Foundation tests.
|
|
Explore Courses for CA Foundation exam
|
|
Suggested Free Tests
Signup for Free!
Signup to see your scores go up within 7 days! Learn & Practice with 1000+ FREE Notes, Videos & Tests.
|
© EduRev
|
Education Revolution
|
Follow Us
|
Signup to see your scores
go up within 7 days!
Access 1000+ FREE Docs, Videos and Tests
Takes less than 10 seconds to signup