!known_y's,known_x's,const,stats!!Returns statistics that describe a linear trend matching known data points, by fitting a straight line using the least squares method!is the set of y-values you already know in the relationship y = mx + b!is an optional set of x-values that you may already know in the relationship y = mx + b!is a logical value: the constant b is calculated normally if Const = TRUE or omitted; b is set equal to 0 if Const = FALSE!is a logical value: return additional regression statistics = TRUE; return m-coefficients and the constant b = FALSE or omitted!
known_y's,known_x's!Calculates the point at which a line will intersect the y-axis by using a best-fit regression line plotted ...
known_y's,known_x's!Returns the slope of the linear regression line through the given data points!is an array or cell range ...
known_y's,known_x's!Returns the square of the Pearson product moment correlation coefficient through the given data points!is ...
known_y's,known_x's!Returns the standard error of the predicted y-value for each x in a regression!is an array or range of ...
known_y's,known_x's,const,stats!Returns statistics that describe a linear trend matching known data points, by fitting a ...
known_y's,known_x's,const,stats!Returns statistics that describe an exponential curve matching known data points!is the set ...
known_y's,known_x's,new_x's,const!Returns numbers in a linear trend matching known data points, using the least squares method!is ...
known_y's,known_x's,new_x's,const!Returns numbers in an exponential growth trend matching known data points!is the set of ...
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