- #1
Roo2
- 47
- 0
Hello,
I have an experiment that I'm trying to conduct where I measure quantity A and normalize by quantity B. I then want to report normalized quantity A with error bars showing standard deviation. Quantity B is obtained via a standard curve that I generated (8 data points measured once each as the independent variable, 8 data points measured 10x as the dependent variable). From this I performed a linear regression, and using Excel's LINEST function, obtained the standard errors of the slope and intercept.
I don't really care about the slope (since I'm normalizing I don't care what the true value of B is; I just need to make sure it's correct relative to the other samples). All I want to do is perform background correction by subtracting the intercept and performing the appropriate error propagation. However, for the error propagation I need the s.d. of the intercept, and LINEST gives me the s.e. For conversion, do I multiply the s.e. by the square root of the number of data points in the regression? Do I subtract 2 from N to account for the lost degrees of freedom? Does it matter that for each independent variable I have 10 measurements of the dependent variable (i.e. is my N going to be 80)?
Thanks for any advice!
I have an experiment that I'm trying to conduct where I measure quantity A and normalize by quantity B. I then want to report normalized quantity A with error bars showing standard deviation. Quantity B is obtained via a standard curve that I generated (8 data points measured once each as the independent variable, 8 data points measured 10x as the dependent variable). From this I performed a linear regression, and using Excel's LINEST function, obtained the standard errors of the slope and intercept.
I don't really care about the slope (since I'm normalizing I don't care what the true value of B is; I just need to make sure it's correct relative to the other samples). All I want to do is perform background correction by subtracting the intercept and performing the appropriate error propagation. However, for the error propagation I need the s.d. of the intercept, and LINEST gives me the s.e. For conversion, do I multiply the s.e. by the square root of the number of data points in the regression? Do I subtract 2 from N to account for the lost degrees of freedom? Does it matter that for each independent variable I have 10 measurements of the dependent variable (i.e. is my N going to be 80)?
Thanks for any advice!