Y-intercept (b): The y-intercept of a line, often written as b, is the value of y at the point where the line crosses the y-axis.
To find the slope of a line, often written as m, take two points on the line, (x1,y1) and (x2,y2) the slope is equal to (y2 - y1)/(x2 - x1). You can describe any straight line with the slope and the y-intercept: Slope (m). The following illustration shows the order in which the additional regression statistics are returned. Compare the values that you find in the table to the F statistic returned by LinEst to determine a confidence level for the model. Use the degrees of freedom to help you find F-critical values in a statistical table. Use the F statistic to determine whether the observed relationship between the dependent and independent variables occurs by chance.
The F statistic, or the F-observed value. At the other extreme, if the coefficient of determination is 0, the regression equation is not helpful in predicting a y-value. If it is 1, there is a perfect correlation in the sample-there is no difference between the estimated y-value and the actual y-value. Compares estimated and actual y-values, and ranges in value from 0 to 1. The standard error value for the constant b (seb = #N/A when const is False). The standard error values for the coefficients m1,m2.,mn. The additional regression statistics are as follows. If stats is False or omitted, LinEst returns only the m-coefficients and the constant b. The m-values are coefficients corresponding to each x-value, and b is a constant value. + b (if there are multiple ranges of x-values), where the dependent y-value is a function of the independent x-values. The equation for the line is y = mx + b or y = m1x1 + m2x2 +. Stats - a logical value specifying whether to return additional regression statistics. Known_x's - an optional set of x-values that you may already know in the relationship y = mx + b.Ĭonst - a logical value specifying whether to force the constant b to equal 0. Known_y's - the set of y-values that you already know in the relationship y = mx + b. LinEst ( Arg1, Arg2, Arg3, Arg4)Įxpression A variable that represents a WorksheetFunction object. Because this function returns an array of values, it must be entered as an array formula. Calculates the statistics for a line by using the least squares method to calculate a straight line that best fits your data, and returns an array that describes the line.