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=LOGEST()

The equation for the curve is: y = b*m^x or y = (b*(m1^x1)*(m2^x2)*_) if there are multiple x-values, where the dependent y-value is a function of the independent x-values. The m-values are bases corresponding to each exponent x-value, and b is a constant value. Note that y, x, and m can be vectors. The array that LOGEST returns is {mn,mn-1,...,m1,b}.

Applies To: Excel for Microsoft 365Excel for Microsoft 365 for MacExcel 2024Excel 2024 for MacExcel 2021Excel 2021 for MacExcel 2019Excel 2016
=LOGEST(known_y's, [known_x's], [const], [stats])
Hover argument names in the table for details.
Output typeArray
Popularity6 / 100
VolatileNo
Dynamic ArrayNo
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◧ Arguments

ArgumentTypeRequiredDescription
known_y's Range Required The set of y-values you already know in the relationship y = b*m^x. If the array known_y's is in a single column, then each column of known_x's is interpreted as a separate variable. If the array known_y's is in a single row, then each row of known_x's is interpreted as a separate variable.
known_x's Range Optional An optional set of x-values that you may already know in the relationship y = b*m^x. The array 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 omitted, it is assumed to be the array {1,2,3,...} that is the same size as known_y's.
const Logical Optional A logical value specifying whether to force the constant b to equal 1. If const is TRUE or omitted, b is calculated normally. If const is FALSE, b is set equal to 1, and the m-values are fitted to y = m^x.
stats Logical Optional A logical value specifying whether to return additional regression statistics. If stats is TRUE, LOGEST returns the additional regression statistics, so the returned array is {mn,mn-1,...,m1,b;sen,sen-1,...,se1,seb;r 2,sey; F,df;ssreg,ssresid}. If stats is FALSE or omitted, LOGEST returns only the m-coefficients and the constant b.

▣ Examples

Example 1 =LOGEST(B2:B25, A2:A25)
Example 2 =INDEX(LOGEST(B2:B25, A2:A25), 1) - 1

§ Remarks

  • The more a plot of your data resembles an exponential curve, the better the calculated line will fit your data. Like LINEST, LOGEST returns an array of values that describes a relationship among the values, but LINEST fits a straight line to your data; LOGEST fits an exponential curve. For more information, see LINEST.
  • When you have only one independent x-variable, you can obtain y-intercept (b) values directly by using the following formula: Y-intercept (b): INDEX(LOGEST(known_y's,known_x's),2) You can use the y = b*m^x equation to predict future values of y, but Microsoft Excel provides the GROWTH function to do this for you. For more information, see GROWTH function.
  • 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 regional settings.
  • 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.

✦ Tips

  • The more a plot of your data resembles an exponential curve, the better the calculated line will fit your data. Like LINEST, LOGEST returns an array of values that describes a relationship among the values, but LINEST fits a straight line to your data; LOGEST fits an exponential curve. For more information, see LINEST.
  • When you have only one independent x-variable, you can obtain y-intercept (b) values directly by using the following formula: Y-intercept (b): INDEX(LOGEST(known_y's,known_x's),2) You can use the y = b*m^x equation to predict future values of y, but Microsoft Excel provides the GROWTH function to do this for you. For more information, see GROWTH function.
  • 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 regional settings.
  • 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.

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