Regression on data entered as mean, n and SD or SEM 

Regression on data entered as mean, n and SD or SEM 


If your data has replicate Y values for each X value, there are two ways to enter the data into Prism. You can enter the raw replicates. Or you can enter mean, n and SD or SEM. How do regression results differ?
• With ordinary nonlinear regression, Prism gives exactly the same results as if you had entered raw data, even with weighted regression. This document explains the mathematical details about how Prism does it.
•If you choose robust nonlinear regression, Prism fits only the means and ignores the n and SD or SEM values you entered.
•If you choose outlier detection, this uses only the information from the means (ignoring n and SD or SEM). But once any outliers are identified and removed (if you chose that), the fitting proceeds as usual and does account for n and SD or SEM.
•If you want Prism to only fit the means with nonlinear regression, this is a choice on the Weights tab. It is
•It is better to enter the raw data so you can plot the raw data to look for outliers or problems. You can then change the graph to plot mean and SD to avoid making the graph too busy.
•If you want to see the SD (or SEM) at each X value, Prism has an analysis for that (Row Means...).