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Basic Question 5 of 14
Which of the following are true about the SEE (standard error of estimate)?
II. Based on squared vertical deviations between Y and Y'
III. Cannot be negative
I. Measure of the accuracy of the prediction
II. Based on squared vertical deviations between Y and Y'
III. Cannot be negative
User Contributed Comments 5
| User | Comment |
|---|---|
| mazen1967 | y bar |
| davidt876 | @mazen: y hat you mean? Also can't the square root of a number be both negative and positive re: answer III? |
| brave1986 | its not the square root but the correlation coefficient raised to the power 2 |
| davidt87 | dude what? this is about SEE not the coefficient of determination. SEE = {E[(Yi - a - bXi)^2/(n-2)]}^(1/2) sq. roots can be negative or positive no? |
| CFAJ | the SEE is a measure of variability away from the estimated values so it would be always be a positive value cos you can't be like negative one foot away from a point if you know what i mean? you are just 1 foot away from that place |
I am using your study notes and I know of at least 5 other friends of mine who used it and passed the exam last Dec. Keep up your great work!
Barnes
Learning Outcome Statements
calculate and interpret measures of fit and formulate and evaluate tests off it and of regression coefficients in a simple linear regression
CFA® 2025 Level I Curriculum, Volume 1, Module 10.