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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 |
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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.