1. It is different, that is,
unstandardized coefficient(β): represents the effect of an independent variable on the dependent variable, net of the effects of the other independent variables

standardized coefficients or beta coefficients are the estimates resulting from an analysis performed on variables that have been standardized (mean=0, variance=1). This is usually done to answer the question of which of the independent variables have a greater effect on the dependent variable in a multiple regression analysis, when the variables are measured in different units of measurement (for example, income measured in dollars and family size measured in number of individuals). There is a big advantage when someone uses beta coefficients. They are directly comparable to one another, with the largest coefficient indicating which independent variable has the greatest influence on the dependent variable. On the other hand is difficult to interpret a linear model using beta coefficients

2. I believe that i gave you the answer.

3. When you say 95% CI = (mean-2se, mean+2se)

Thank you very much! mssr. Your suggestions are really helpful!

One more question: is that means that if I use standardized coefficient, I cannot calculate the 95%CI for this coefficient, or according to 95%CI=mean-2se, mean+2se, the 95%CI for standardized coefficient would be (-2se, se), since mean=0?

Thanks!

No you must follow the formula:  StdBeta +/- 2*SE(StdBeta). In SPSS you cannot find, but in STATA you can use The simplest way is using the formula: SE(StdBeta_i) =[SD(Y)/SD(X_i)]*SE(beta_i) all of those numbers are available from regressoutput. Also, you could running a "regress" command using the standardized Xs variables in place of the original variables.

It's really really nice to meet you, mssr. Thank you very much!
I wondered if you could detail the process and the command how to calculate the StdBeta 95% CI by using STATA.
if:
Idependent variable: CRP
Dependent variable: TT
Adjusted variable: Age

Thank you very very much !

First of all the formula is [SD(x_i)/SD(y)]*SE(beta_i). I am really sorry.

The Stata command is:

1. regress TT CRP Age full beta

After that:
2. You will use the command "listcoef".The listcoef command gives more extensive output regarding standardized coefficients. It is not part of Stata, but you can download it over the internet like this

findit listcoef

and after installation you will see a more annotated output which gives you the same output with regress but with more four columns. (bStdX    bStdY   bStdXY      SDofX) You will notice in stata output that bStdXY is the same with Beta coefficient from previous output.