Hi I am trying to find the relationship between two variables. First I fitted a linear model between two variables and I found the following results: Residual standard error: 0.03253 on 2498 degrees of freedom Multiple R-squared: 0.5551, Adjusted R-squared: 0.5549 F-statistic: 3116 on 1 and 2498 DF, p-value: < 2.2e-16 Then I used the cor function to see the correlation between two variable I get the following result -0.7450344 How can we interpret the result based on R-squared and correlation ? From the p-value we can see that there is very strong relationship between variables as it is way less that 0.001 Can anyone kindly explain the difference between Multiple R squared, adjusted R-squared and correlation and how to report these values while writing a report ? Thank you so much. [[alternative HTML version deleted]]
On 15 February 2013 21:26, Janesh Devkota <janesh.devkota@gmail.com> wrote:> Hi I am trying to find the relationship between two variables. > > First I fitted a linear model between two variables and I found the > following results: > Residual standard error: 0.03253 on 2498 degrees of freedom > Multiple R-squared: 0.5551, Adjusted R-squared: 0.5549 > F-statistic: 3116 on 1 and 2498 DF, p-value: < 2.2e-16 > > Then I used the cor function to see the correlation between two variable > I get the following result > -0.7450344 > >r is a correlation (it actually stands for regression). R (upper case) is a multiple correlation. But you only have one predictor, so it's a correlation. R squared is R (or r), squared. So -0.7450433^2 = 0.555.> How can we interpret the result based on R-squared and correlation ? From > the p-value we can see that there is very strong relationship between > variables as it is way less that 0.001 > >The p-value doesn't tell you about the strength of the relationship.> Can anyone kindly explain the difference between Multiple R squared, > adjusted R-squared and correlation and how to report these values while > writing a report ? > >I can suggest a number of books that do this much better than I could in an email. But you probably have a favorite of your own. Jeremy [[alternative HTML version deleted]]
On Feb 15, 2013, at 9:26 PM, Janesh Devkota wrote:> Hi I am trying to find the relationship between two variables. > > First I fitted a linear model between two variables and I found the > following results: > Residual standard error: 0.03253 on 2498 degrees of freedom > Multiple R-squared: 0.5551, Adjusted R-squared: 0.5549 > F-statistic: 3116 on 1 and 2498 DF, p-value: < 2.2e-16 > > Then I used the cor function to see the correlation between two > variable > I get the following result > -0.7450344 > > How can we interpret the result based on R-squared and correlation ? > From > the p-value we can see that there is very strong relationship between > variables as it is way less that 0.001 > > Can anyone kindly explain the difference between Multiple R squared, > adjusted R-squared and correlation and how to report these values > while > writing a report ?This is not an on-topic question for this mailing list. The CrossValidated website is more likely to respond as you might have wished. (Please read the Posting Guide.) -- David Winsemius, MD Alameda, CA, USA