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<< Click to Display Table of Contents >> INTERCEPT (intercept point of a regression line) |
Syntax:
INTERCEPT(y_values, x_values)
Description:
This 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 (called "trendline" or "best-fit line") to a set of data points (for example, the results of a series of measurements).
You can use the INTERCEPT function to predict what y (the dependent variable) will be approximately if x (the independent variable) is zero.
This function can be used to predict, for example, the resistance of a temperature-dependent resistor at 0° after having measured the resistance at several other temperatures.
For the arguments y_values and x_values, you usually specify a cell range.
y_values are the dependent variables (the resistance in the above example).
x_values are the independent variables (the temperature in the above example).
Note:
Note that this function expects the y_values first and then the x_values – not the other way around.
Additional info:
The linear regression is performed with this function using the least squares method.
Example:
The resistance of a temperature-dependent resistor has been measured at several temperatures.
Cells A1:A4 contain the temperatures that were measured (the independent variables): 8, 20, 25, 28
Cells B1:B4 contain the resistances that were measured (the dependent variables): 261, 508, 608, 680
The resistance which will be delivered at 0°C can be estimated using the following formula:
INTERCEPT(B1:B4, A1:A4) returns 93.69817
At 0°, a resistance of 93.69817 (Ohm) would thus be expected.
Additional info:
INTERCEPT(y_values, x_values) equals FORECAST(0, y_values, x_values).
See also: