An analyst performs a simple regression of the price of W. Byrd stock versus the S&P 500 using monthly data points. THe regression results give a sum of squares regression (MSR) of 2,700 and sum of squared errors (SSE) of 300. The Standard error of estimate, SEE = sqrt(300/58) = .719. Based on this infromation the analyst must deterime the number of months used to run the regression and must calculate the coeffient of determination. Which of the following choices is closest to the correct information Number of Months R-squared A. 59 .90 B. 59 .95 C. 60 .90 D. 60 .95 having trouble deteriming the R-squared here.
R^2 = coeff of determination = MSR / (MSR + SSE) = 2700/3000 = .9 Number of months = n + 2 = 58 + 2 = 60 Choice C
MSR usually is mean square regression which is SSR/df.
Besides SEE the CFA text didn’t have any of these stupid acronyms.
SSR = 2700 SSE = 300 SEE = Sqrt(SSE/ n-2) SEE = sqrt(300/58) therefore n-2 = 58 n=60 CoD = R2 = (explained) / total CoD = SSR (explained)/ (SSR(explained) + SSE(unexplained)) CoD = 2700/ (2700 + 300) CoD = 0.9 S&P 500 explains 90% of the variaotion in the W. Byrd stock… Answer is C - Dinesh S
great explaination Dinesh
yea…i find remembering the full terms easier than remembering the SEE,SSE,SSR,SST etc…