| | | This function can return an array |
| | | In regression analysis, calculates an exponential curve that fits your data and returns an array of values that describes the curve. Because this function returns an array of values, it must be entered as an array formula. |
| | | This function returns an array of values that best describes a relationship among the values. |
| | | If "known_y's" is in a single column, then each column of "known_x's" is interpreted as a separate variable. |
| | | If "known_y's" is in a single row, then each row of "known_x's" is interpreted as a separate variable. |
| | | The "known_x's" can include one or more sets of variables. |
| | | If only one variable is used, known_y's and known_x's can be ranges of any shape, as long as they have equal dimensions. |
| | | If more than one variable is used, known_y's must be a range of cells with a height of one row or a width of one column (which is also known as a vector). |
| | | If "known_x's" is left blank, then it is assumed to be the array {1,2,3,...} that is the same size as "known_y's". |
| | | If "const" = True, then b is calculated normally. |
| | | If "const" = False, b is set equal to 1, and the m-values are fitted to y = m^x. |
| | | If "const" is left blank, then True is used. |
| | | If "stats" = True, then additional regression statistics are returned (i.e. the array is {mn,mn-1,...,m1,b;sen,sen-1,...,se1,seb;r 2,sey; F,df;ssreg,ssresid} ). |
| | | If "stats" = False, then only the m-coefficients and the constant b are returned. |
| | | If "stats" is left blank, then False is used. |
| | | The more a plot of your data resembles an exponential curve, the better the calculated line will fit your data. |
| | | Formulas that return arrays must be entered as array formulas |
| | | When entering an array constant such as "known_x's" as an argument, use commas to separate values in the same row and semicolons to separate rows. Separator characters may be different depending on your country setting. |
| | | You should note that the y-values predicted by the regression equation may not be valid if they are outside the range of y-values you used to determine the equation. |
