Exponential regression calculator
Fit y = a·e^(bx) to positive Y values by linearising ln(Y).
Fit on the original scale
| Row | X | Y | Fitted value | Residual |
|---|---|---|---|---|
| Fill in the fields above — the result is computed on this page. | ||||
How do I use this page?
- Paste X and positive Y values.
- Read a, b and the factor e^b.
- Review R-squared, RMSE and residuals on the Y scale.
What this page does not do: Every Y value must be positive. Log linearisation minimises errors in the log scale; it is not identical to nonlinear least squares that minimises errors directly on the Y scale.
Further reading
Theory — what is exponential regression?
Exponential regression suits processes where change is proportional to the current value. The calculator fits a straight line to the logged data ln(Y), then transforms the result back into the equation y = a·e^(bx). The value e^b is a multiplier describing how many times Y grows or shrinks when X increases by one. A key limitation is that Y must be positive, since the logarithm of zero or a negative number is not defined in real numbers.
Frequently asked questions
Why can Y not equal zero?
What does e^b = 1.05 mean?
See also
A/B test calculator
Compare two proportions in an A/B test. Calculate conversion rates, difference, uplift, z score, p value and c
A/B test planning — sample size, MDE and duration
Plan a two-proportion experiment, estimate detectable effect and traffic duration.
ACF and PACF autocorrelation calculator
Calculate ACF and PACF across time-series lags. Review the chart, reference bounds and coefficient table.