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  • is the set of dependent data
  • is the set of independent data.


  • This function is calculating the point where the line is intersecting y-axis using dependent and independent variables.
  • Using this function we can find the value of when is zero.
  • The intercept point is finding using simple linear regression.
  • It is fits a straight line through the set of points in such a way that makes vertical distances between the points of the data set and the fitted line as small as possible.
  • Regression methods nearly to the simple ordinary least squares also exist.
  • i.e.,The Least Squares method relies on taking partial derivatives with respect to the slope and intercept which provides a solvable pair of equations called normal equations.
  • Suppose there are data points , where
  • To find the equation of the regression line:.
  • This equation will give a "best" fit for the data points.
  • The "best" means least-squares method. Here b is the slope.
  • The slope is calculated by:.
  • In this formula and are the sample means AVERAGE of and .
  • In , the arguments can be numbers, names, arrays, or references that contain numbers.
  • The arrays values are disregarded when it is contains text, logical values or empty cells.
  • This function will return the result as error when any one of the argument is non-numeric or and is having different number of data points and there is no data.

ZOS Section

  • The syntax is to calculate intercept of the regreesion line in ZOS is .
    • is the set of dependent data
    • is the set of independent data.
  • For e.g.,intercept([14,16,19,15.25],[20.1,26,10,26.4])


1 4 5 2 10
2 12 20 15 11
3 25 -12 -9 30 18
4 10 15 -40 52 36
  1. =INTERCEPT(A1:D1,A2:D2)= 10.13265306
  2. =INTERCEPT(A3:E3,A4:E4)= 4.754939085

See Also