Question

How might squaring a correlation coefficient be useful to understanding the relationship between two variables? Why...

  1. How might squaring a correlation coefficient be useful to understanding the relationship between two variables?
  2. Why is it important to remember “association, not causation” when discussing correlations? Please provide an example.

Homework Answers

Answer #1

Suppose the correlation coefficient between X and Y is -0.9 and that between X and Z is 0.3. It is difficult to compare the correlation between X, Y and X, Z. Now if we look into the square of correlation coefficient ie r2. We see that for X and Y, r2 = 0.81 and for X, Z, r2 takes value 0.09. Now it is possible to see which relationship is much stronger.

Suppose we find that the correlation coefficient between "marks obtained by girls" and "marks obtained by boys" in a particular subject is 0.9. We can say that the association between two variable is high enough. But we cannot tell that the marks obtained by girls is highly affected by the marks obtained by boys because both boys and girls studied and had given exams independently of each other. So if we interpret the correlation coefficient as a causation then the interpretation becomes meaningless.

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
How might squaring a correlation coefficient be useful to understanding the relationship between two variables?
How might squaring a correlation coefficient be useful to understanding the relationship between two variables?
Provided a detailed summary of what the squaring of a correlation coefficient be useful to understanding...
Provided a detailed summary of what the squaring of a correlation coefficient be useful to understanding the relationship between two variables Only partially provided a summary of what the squaring of a correlation coefficient be useful to understanding the relationship between two variables
Why is it important to remember “association, not causation” when discussing correlations? Please provide an example.
Why is it important to remember “association, not causation” when discussing correlations? Please provide an example.
Why is it advisable to generate a scatterplot before computing a correlation coefficient between two variables?...
Why is it advisable to generate a scatterplot before computing a correlation coefficient between two variables? Describe how a scatterplot might differ when viewing correlations that represent positive, negative, and no relationship between predictor and criterion variables. Is it possible to have a relation between variables that systematic (i.e., reliable and predictable) yet not linear?
A Correlation Coefficient is a measurement of the relationship between two variables. A positive correlation means...
A Correlation Coefficient is a measurement of the relationship between two variables. A positive correlation means that as one variable increases, the second variable increases too. A negative correlation means that as one variable increases, the second variable decreases, or as one variable decreases, the second variable increases. Positive and negative correlations exists in nature, science, business, as well as a variety of other fields. Please watch the following video for a graphical explanation of the correlation coefficient: For Discussion...
One of the major misconceptions about correlation is that a relationship between two variables means causation;...
One of the major misconceptions about correlation is that a relationship between two variables means causation; that is, one variable causes changes in the other variable. There is a particular tendency to make this causal error, when the two variables seem to be related to each other. What is one instance where you have seen correlation misinterpreted as causation? Please describe. an orginal post please
One of the major misconceptions about correlation is that a relationship between two variables means causation;...
One of the major misconceptions about correlation is that a relationship between two variables means causation; that is, one variable causes changes in the other variable. There is a particular tendency to make this causal error, when the two variables seem to be related to each other. What is one instance where you have seen correlation misinterpreted as causation? Please describe Can you help me understand how to answer this question
Describe the relationship between two variables when the correlation coefficient r is near 0.
Describe the relationship between two variables when the correlation coefficient r is near 0.
Discussion 1: Searching for Causes This week examines how to use correlation and simple linear regression...
Discussion 1: Searching for Causes This week examines how to use correlation and simple linear regression to test the relationship of two variables. In both of these tests you can use the data points in a scatterplot to draw a line of best fit; the closer to the line the points are the stronger the association between variables. It is important to recognize, however, that even the strongest correlation cannot prove causation. For this Discussion, review this week’s Learning Resources...
a brief explanation of when an observed correlation might represent a true relationship between variables and...
a brief explanation of when an observed correlation might represent a true relationship between variables and why. Be specific and provide examples. must relate to public health.