| Applying science to business management |
   
stderror
Format: stderror( [x1,x2,...],
y, zero )
Arguments: [real] [x1,x2] Lists of
independent values
[real] y List of dependent values
(bool) zero Optional zero y-intercept;
default = no
Returns: [real] List including the standard error for
each regression coefficient b, m1, m2, ..., mn
Description: The standard error for a least-squares
regression coefficient is a measure of how well the coefficient
matches the input data points. More specifically, it represents
the standard deviation of the regression coefficient.
Stderror is designed to be used in conjunction with linefit.
Examples: Fit a line of the form y(x)=b+m*x to
the data points:
(1,7), (3,15), (4,14), (7,20), and (8,30).
and calculate the standard error for each coefficient.
x:=[1,3,4,7,8]
y:=[7,15,14,20,30]
stderror(x,y) = [3.06,0.58]
See Also: linefit,
rsquared
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