Say I have a linear fit given y = ax + b. I'm given Δa and Δb as 95% confidence intervals.
I now have several measurements y1, y2, y3, ... etc, from which of course I can gather a mean, standard deviation and confidence interval. If I want to find some x and its uncertainty from these, how should I go about this.
It's easy to get an expected value for x, from some simple algebra.
x = (y-b)/a
I use the mean of y for this calculation.
But going through the error propagation
$ \Delta x = x*\sqrt{(\frac{\sqrt{\Delta y^2 + \Delta b^2}}{y-b})^2+ (\frac{\Delta a}{a})^2}$
I'm unsure what numbers I should be using for the Deltas in this case. Should it be the confidence intervals or standard deviations? I intuit that it should be the standard deviations but I'm unsure how to get those without any information from the original fit.
Thanks in advance.