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<< Click to Display Table of Contents >> INTERCEPT (intercept point of a regression line) |
Syntax:
INTERCEPT(y_values, x_values)
Description:
Returns the y coordinate of the point where a best-fit line based on the given values intersects the y axis.
A best-fit line is the result of a linear regression. This is a statistical technique that adapts a line to a set of data points (for example, the results of a series of measurements).
With the INTERCEPT function, you can predict what y (the dependent variable) will be approximately when x (the independent variable) is zero.
This function can be used to predict, for example, the resistance of a temperature-sensitive resistor at 0° after having measured the resistance at several other temperatures.
For the y_values and x_values arguments, you usually specify a cell range.
y_values are the known y values (e.g., the resistance).
x_values are the known x values (e.g., the temperature).
Note:
Note that this function expects the y_values first and then the x_values – not the other way around.
Annotation:
The linear regression is performed with this function using the least squares method.
Example:
The resistance of a temperature-sensitive resistor has been measured at several temperatures.
Cells A1:A4 contain the temperatures measured: 8, 20, 25, 28
Cells B1:B4 contain the resistances measured: 261, 508, 608, 680
With the following formula you can estimate which resistance will be delivered at 0°C:
INTERCEPT(B1:B4, A1:A4) equals 93.69817
So at 0° a resistance of 93.69817 (Ohm) would be expected.
Annotation:
INTERCEPT(y_values, x_values) equals FORECAST(0, y_values, x_values).
See also: