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Question:
Answers:http://en.wikipedia.org/wiki/Coefficient_of_determination#Adjusted_R2
Answers:http://en.wikipedia.org/wiki/Coefficient_of_determination#Adjusted_R2
Question:My homework assignment says I can calculate the basic R2 based on the data given, to determine which of the two has a higher R2
Equation 1: adjusted R2 is .624 and N is 41
Equation 2: adjusted R2 is .532 and N is 44
Wouldn't R2 be higher for equation 1? The difference in degrees of freedom is so small it couldn't be enough for a .10 swing. Still curious how the calculation would be done!
Thanks!
Answers:http://en.wikipedia.org/wiki/Coefficient_of_determination#Adjusted_R2 gives the formula. If A is adjusted Rsquared and R2 is ordinary Rsquared, wikipedia gives: A = 1(1R2) (n1)/(np1) rearranging: R2 = 1(1A) (np1)/(n1) where p is the number of parameters (not counting the constant term) in the regression.
Answers:http://en.wikipedia.org/wiki/Coefficient_of_determination#Adjusted_R2 gives the formula. If A is adjusted Rsquared and R2 is ordinary Rsquared, wikipedia gives: A = 1(1R2) (n1)/(np1) rearranging: R2 = 1(1A) (np1)/(n1) where p is the number of parameters (not counting the constant term) in the regression.
Question:I am looking for a basic definition of the statistics term: Adjusted R^2. I just need a simple down to earth example that applies to life demonstrating the concept. Thank you.
Answers:I suppose you mean an adjusted correlation coefficient? try here:
Answers:I suppose you mean an adjusted correlation coefficient? try here:
Question:From a multiple regression analysis of stock market data, the following ANOVA table output was obtained from EXCEL.
df SS MS F
Regression 2 97.21 48.605 12.72186
Residual 17 64.95 3.820588
Total 19 162.16
Answers:First you need Rsquared RSquared = 1  SS(E)/SS(T) = 1 64.95/162.16 = .40053 Adjusted = 1  (1Rsquared)(n1)/(np1) So a stab at this is = 1  (.40053)(19)/17 = 0.552348 You need to check my n1 and np1, but the idea is there
Answers:First you need Rsquared RSquared = 1  SS(E)/SS(T) = 1 64.95/162.16 = .40053 Adjusted = 1  (1Rsquared)(n1)/(np1) So a stab at this is = 1  (.40053)(19)/17 = 0.552348 You need to check my n1 and np1, but the idea is there
From Youtube
Regression 3: Sums of Squares and Rsquared :In this video, I give two formulas for r^2, and give one intuitive interpretation of the value of r^2.