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Basic Question 5 of 14

Which of the following are true about the SEE (standard error of estimate)?

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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Tamara Schultz

Tamara Schultz

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® 2024 Level I Curriculum, Volume 1, Module 10.