- is the set of dependent data
- is the set of independent data.
- This function is calculating the point where the line is intesecting 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 i = 1, 2, …, n.
- 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: 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 nonnueric or x and y is having different number of data points and there is no data.
Where Y is the dependent set of observations or data, and
Y is the independent set of observations or data.
This function calculates the point at which a line will intersect the y-axis using the available x-values and y-values.
· An array contains text, logical values, or empty cells that are ignored; but, the cells with the value zero are included.
· INTERCEPT shows the error value, when Y and X have a dissimilar number of data points.
· The equation to calculate the intercept of the regression line, a, is:
where b is the slope, and is calculated as:
and where x and y are the sample means AVERAGE(Y) and AVERAGE(X).
Lets see an example,
=INTERCEPT(B2:B6,C2:C6) is 1.2268