I know it is root mean square.

For example a,b,c,d,e,f

RMS=sqrt((a*a+b*b+c*c+d*d+e*e+f*f)/6)

Is it right?

If you mean the RMS defined in an histogram, it is the standard deviation,

not the root mean square,

[quote=â€śmonetaâ€ť]If you mean the RMS defined in an histogram, it is the standard deviation,

not the root mean square,

see root.cern.ch/root/html/TH1.html#TH1:GetRMS[/quote]

I find RMS in Users_Guide_5_12.pdf

see root.cern.ch/root/doc/RootDoc.html

page 57.Statistics Display:

the root mean square (RMS)

IS it right?

could you tell me all the meaning of â€śthe 7 statistic displayâ€ť in my plot?

thanks!

i fit the histogramm with gaus

As I said before, the meaning of RMS is standard deviation. This is common in physics, as it is mentioned also in

mathworld.wolfram.com/Root-Mean-Square.html

I agree, we should indicate that clearly also in the User guide.

Concerning the picture:

Mean: Average of the histogram entries

RMS: Standard deviation of the histogram entries

Chi2: Chi2 value obtained from the fit :

Sum squares of the normalized residuals :

```
Sum [( bin content - function value)/binError]^2
```

ndf : number of degree of freedom in the fit =

number of bins used in calculating the chi2 - number of fit parameters

then we have the fitted parameters :

Constant: is the amplitude of the fitted Gaussian function

Mean : is the mean of the gaussian

sigma: standard deviation of the gaussian

In case of perfect gaussian data and infinite statistics RMS -> sigma

I hope it is clear,

Regards,

Lorenzo

[quote=â€śmonetaâ€ť]As I said before, the meaning of RMS is standard deviation. This is common in physics, as it is mentioned also in

mathworld.wolfram.com/Root-Mean-Square.html

I agree, we should indicate that clearly also in the User guide.

Concerning the picture:

Mean: Average of the histogram entries

RMS: Standard deviation of the histogram entries

Chi2: Chi2 value obtained from the fit :

Sum squares of the normalized residuals :

```
Sum [( bin content - function value)/binError]^2
```

ndf : number of degree of freedom in the fit =

number of bins used in calculating the chi2 - number of fit parameters

then we have the fitted parameters :

Constant: is the amplitude of the fitted Gaussian function

Mean : is the mean of the gaussian

sigma: standard deviation of the gaussian

In case of perfect gaussian data and infinite statistics RMS -> sigma

I hope it is clear,

Regards,

Lorenzo[/quote]

Yout are kind to me!

Thanks !

I am a student of China.And my professor did no know the meaning of RMS ,so i have to learn of them.So i tell him!

Wish you best!

Do you know Chinese?