Linear Regression

Functions > Data Analysis > Curve Fitting > Linear Regression

Linear Regression

• line(vx, vy)—Returns a vector containing the coefficients a and b for a line of the form a + b·x that best approximates the data in vectors vx and vy in the least-squares sense.

• slope(vx, vy)—Returns the slope of line that best fits data in vx and vy.

• intercept(vx, vy)—Returns the intercept of line that best fits data in vx and vy.

• stderr(vx,vy)—Returns the standard error associated with a linear regression for the points in vx and vy. It measures how closely data points are spread about the regression line using the following formula:

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where n = rows(vx) = rows(vy).

Watch this video to learn more about linear regression:

Arguments

• vx is a vector of real numbers representing the x values.

• vy is a vector of real numbers representing the y values. vy must be the same length as vx.