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When plotted in the manner described above, the value of the y-intercept (at = / =) will correspond to (), and the slope of the line will be equal to /. The values of y-intercept and slope can be determined from the experimental points using simple linear regression with a spreadsheet .
A meteoric water line can be calculated for a given area, named as local meteoric water line (LMWL), and used as a baseline within that area. Local meteoric water line can differ from the global meteoric water line in slope and intercept. Such deviated slope and intercept is a result largely from humidity.
The best known plots of the Michaelis–Menten equation, including the double-reciprocal plot of / against /, [2] the Hanes plot of / against , [3] and the Eadie–Hofstee plot [4] [5] of against / are all plots in observation space, with each observation represented by a point, and the parameters determined from the slope and intercepts of the lines that result.
The intercept and slope of a linear regression between the quantiles gives a measure of the relative location and relative scale of the samples. If the median of the distribution plotted on the horizontal axis is 0, the intercept of a regression line is a measure of location, and the slope is a measure of scale.
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The regression line goes through the center of mass point, (¯, ¯), if the model includes an intercept term (i.e., not forced through the origin). The sum of the residuals is zero if the model includes an intercept term: = ^ =
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Many statistical inference procedures for linear models require an intercept to be present, so it is often included even if theoretical considerations suggest that its value should be zero. Sometimes one of the regressors can be a non-linear function of another regressor or of the data values, as in polynomial regression and segmented regression .