nlinfit estimating the standard deviation of parameters

Hello, I want to obtain standard deviation of coefficients after using curve fitting. I'm using [beta,R,J,CovB,MSE,ErrorModelInfo] = nlinfit(X,Y,modelfun,beta0)

1) I understand that standard deviation is not the same as standard error. Correct?

2) For me CovB is a covariance matrix, so on the diagonal should be (standard error)^2 . So I was thinking that sqrt(diag(CovB)) is a standard error of coeficients. However in the manual it is descibed that sqrt(diag(CovB)) is a coefficient standard errors.

My question is: A) if sqrt(diag(CovB)) is a standard error or standard deviation? Because I'm confused by the manual.

B) How to calculate the standard error? Should I multiply sqrt(diag(CovB)) by squere root of samples?

I'm not familiar with statistics so maybe I don't understend the difference between standard deviation is not the same as standard error for coeficients of fit. If so I would apreciate an explanation. Thank you for your help.