Manuals/calci/INTERCEPT
INTERCEPT (KnownYArray,KnownXArray)
- is the set of dependent data
- is the set of independent data.
- INTERCEPT(),returns the intercept of the linear regression line.
Description
- 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
- The syntax is to calculate intercept of the regression 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])
Examples
A | B | C | D | E | |
---|---|---|---|---|---|
1 | 4 | 5 | 2 | 10 | |
2 | 12 | 20 | 15 | 11 | |
3 | 25 | -12 | -9 | 30 | 18 |
4 | 10 | 15 | -40 | 52 | 36 |
- =INTERCEPT(A1:D1,A2:D2)= 10.13265306
- =INTERCEPT(A3:E3,A4:E4)= 4.754939085
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References