But one must not forget that this is only an auxiliary construct - not a necessary one. Of course it is the common idea to the work with the logarithms of your test (Y) values when you suspect an exponential or power based relationship to your X values. Some more words about what I called the 'irrelevance' of the LN(Y) values. Sorry, I should have included a more enligthening example from the start myself, but for some reason this forum won't let me do this.
The reason why you arrive at the same result as the Excel diagram does is, that you do the same thing: calculating the R² between the LN(Y) values and the approximating linear function. The LN(Y) values are irrelevant, because you are interested in how well does your exponential fit behave (and not some intermediate auxiliary function like the logarithm of your Y values). The correlation coefficient should be calculated between your original Y values and the values generated by the approximating exponential function. I used the function CORREL (correlation coefficient), or rather its square. Jump to Approximations - There have been a number of approximations for the exponential integral function. The Microsoft Visual Basic editor window appears. It can be evaluated by polynomial and rational approximations given by Abramowitz and Stegun (1970, p. The function E1(u) is known as the exponential integral. Introduces a method of aquifer test using Excel spreadsheet. These include The Swamee and Ohija approximation =. There have been a number of approximations for the exponential integral function. Exponential Regression using Microsoft Excel. Exponential integral function approximation. Woodwork City pizza of Sarasota Exponential Integral Function Excel.
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