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Nick Cox
Nick Cox
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So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on Stata. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0:   log likelihood = -740.34659  
Iteration 1:   log likelihood = -701.33221  
Iteration 2:   log likelihood = -700.87747  
Iteration 3:   log likelihood = -700.87744  

Probit regression                                 
Number of obs   =       1989
                                                  
LR chi2(1)      =      78.94
                                                  
Prob > chi2     =     0.0000

Log likelihood = -700.87744                       

Pseudo R2       =     0.0533

for the variable white:

Coef.: .7839465  
Std. Err.: .0867118  
z: 9.04  
P>|z|: 0.000  
95% Conf. Interval: .6139946-.9538985

for the constant:

Coef.: .5469463  
Std. Err.: .075435  
z: 7.25  
P>|z|: 0.000  
95% Conf. Interval: .3990964-.6947962

So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on Stata. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0:   log likelihood = -740.34659  
Iteration 1:   log likelihood = -701.33221  
Iteration 2:   log likelihood = -700.87747  
Iteration 3:   log likelihood = -700.87744  

Probit regression                                 
Number of obs   =       1989
                                                  
LR chi2(1)      =      78.94
                                                  
Prob > chi2     =     0.0000

Log likelihood = -700.87744                       

Pseudo R2       =     0.0533

for the variable white:

Coef.: .7839465  
Std. Err.: .0867118  
z: 9.04  
P>|z|: 0.000  
95% Conf. Interval: .6139946-.9538985

for the constant:

Coef.: .5469463  
Std. Err.: .075435  
z: 7.25  
P>|z|: 0.000  
95% Conf. Interval: .3990964-.6947962

I'm not sure how to interpret this probit regression I ran on Stata. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0:   log likelihood = -740.34659  
Iteration 1:   log likelihood = -701.33221  
Iteration 2:   log likelihood = -700.87747  
Iteration 3:   log likelihood = -700.87744  

Probit regression                                 
Number of obs   =       1989
                                                  
LR chi2(1)      =      78.94
                                                  
Prob > chi2     =     0.0000

Log likelihood = -700.87744                       

Pseudo R2       =     0.0533

for the variable white:

Coef.: .7839465  
Std. Err.: .0867118  
z: 9.04  
P>|z|: 0.000  
95% Conf. Interval: .6139946-.9538985

for the constant:

Coef.: .5469463  
Std. Err.: .075435  
z: 7.25  
P>|z|: 0.000  
95% Conf. Interval: .3990964-.6947962
formatting changes.
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edit approved Nov 6, 2012 at 5:05
tchakravarty
edit approved Nov 6, 2012 at 5:05
tchakravarty
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How do I interpret a probit model on STATAin Stata?

So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on STATAStata. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0: log likelihood = -740.34659
Iteration 1: log likelihood = -701.33221
Iteration 2: log likelihood = -700.87747
Iteration 3: log likelihood = -700.87744

Probit regression
Number of obs = 1989

LR chi2(1) = 78.94

Prob > chi2 = 0.0000

Log likelihood = -700.87744

Pseudo R2 = 0.0533

. probit approve white

Iteration 0:   log likelihood = -740.34659  
Iteration 1:   log likelihood = -701.33221  
Iteration 2:   log likelihood = -700.87747  
Iteration 3:   log likelihood = -700.87744  

Probit regression                                 
Number of obs   =       1989
                                                  
LR chi2(1)      =      78.94
                                                  
Prob > chi2     =     0.0000

Log likelihood = -700.87744                       

Pseudo R2       =     0.0533

for the variable white:
Coef.: .7839465
Std. Err.: .0867118
z: 9.04
P>|z|: 0.000
95% Conf. Interval: .6139946-.9538985

Coef.: .7839465  
Std. Err.: .0867118  
z: 9.04  
P>|z|: 0.000  
95% Conf. Interval: .6139946-.9538985

for the constant:
Coef.: .5469463
Std. Err.: .075435
z: 7.25
P>|z|: 0.000
95% Conf. Interval: .3990964-.6947962

Coef.: .5469463  
Std. Err.: .075435  
z: 7.25  
P>|z|: 0.000  
95% Conf. Interval: .3990964-.6947962

How do I interpret a probit model on STATA?

So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on STATA. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0: log likelihood = -740.34659
Iteration 1: log likelihood = -701.33221
Iteration 2: log likelihood = -700.87747
Iteration 3: log likelihood = -700.87744

Probit regression
Number of obs = 1989

LR chi2(1) = 78.94

Prob > chi2 = 0.0000

Log likelihood = -700.87744

Pseudo R2 = 0.0533

for the variable white:
Coef.: .7839465
Std. Err.: .0867118
z: 9.04
P>|z|: 0.000
95% Conf. Interval: .6139946-.9538985

for the constant:
Coef.: .5469463
Std. Err.: .075435
z: 7.25
P>|z|: 0.000
95% Conf. Interval: .3990964-.6947962

How do I interpret a probit model in Stata?

So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on Stata. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0:   log likelihood = -740.34659  
Iteration 1:   log likelihood = -701.33221  
Iteration 2:   log likelihood = -700.87747  
Iteration 3:   log likelihood = -700.87744  

Probit regression                                 
Number of obs   =       1989
                                                  
LR chi2(1)      =      78.94
                                                  
Prob > chi2     =     0.0000

Log likelihood = -700.87744                       

Pseudo R2       =     0.0533

for the variable white:

Coef.: .7839465  
Std. Err.: .0867118  
z: 9.04  
P>|z|: 0.000  
95% Conf. Interval: .6139946-.9538985

for the constant:

Coef.: .5469463  
Std. Err.: .075435  
z: 7.25  
P>|z|: 0.000  
95% Conf. Interval: .3990964-.6947962
deleted 211 characters in body
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Kyle
Kyle
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So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on STATA. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0: log likelihood = -740.34659
Iteration 1: log likelihood = -701.33221
Iteration 2: log likelihood = -700.87747
Iteration 3: log likelihood = -700.87744

Probit regression
Number of obs = 1989

LR chi2(1) = 78.94

Prob > chi2 = 0.0000

Log likelihood = -700.87744

Pseudo R2 = 0.0533

 approve |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]

for the variable white:
Coef.: .7839465
Std. Err.: .0867118
z: 9.04
P>|z|: 0.000
95% Conf. Interval: .6139946-.9538985

-------------+---------------------------------------------------------------- white | .7839465 .0867118 9.04 0.000 .6139946 .9538985 _cons | .5469463 .075435 7.25 0.000 .3990964 .6947962

for the constant:
Coef.: .5469463
Std. Err.: .075435
z: 7.25
P>|z|: 0.000
95% Conf. Interval: .3990964-.6947962

So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on STATA. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0: log likelihood = -740.34659
Iteration 1: log likelihood = -701.33221
Iteration 2: log likelihood = -700.87747
Iteration 3: log likelihood = -700.87744

Probit regression
Number of obs = 1989

LR chi2(1) = 78.94

Prob > chi2 = 0.0000

Log likelihood = -700.87744

Pseudo R2 = 0.0533

 approve |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]

-------------+---------------------------------------------------------------- white | .7839465 .0867118 9.04 0.000 .6139946 .9538985 _cons | .5469463 .075435 7.25 0.000 .3990964 .6947962

So I'm trying to study for an exam and I'm not sure how to interpret this probit regression I ran on STATA. The data is on loan approval and white is a dummy variable that =1 if a person was white, and =0 if the person was not. Any help on how to read this would be greatly appreciated. What I'm mostly looking for is how to find the estimated probability of loan approval for both whites and nonwhites. Can someone also help me with the text on here and how to make it normal?? I'm sorry I don't know how to do this.

. probit approve white

Iteration 0: log likelihood = -740.34659
Iteration 1: log likelihood = -701.33221
Iteration 2: log likelihood = -700.87747
Iteration 3: log likelihood = -700.87744

Probit regression
Number of obs = 1989

LR chi2(1) = 78.94

Prob > chi2 = 0.0000

Log likelihood = -700.87744

Pseudo R2 = 0.0533

for the variable white:
Coef.: .7839465
Std. Err.: .0867118
z: 9.04
P>|z|: 0.000
95% Conf. Interval: .6139946-.9538985

for the constant:
Coef.: .5469463
Std. Err.: .075435
z: 7.25
P>|z|: 0.000
95% Conf. Interval: .3990964-.6947962

added 12 characters in body
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Kyle
Kyle
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  • 16
  • 22
Source Link
Kyle
Kyle
  • 1.2k
  • 6
  • 16
  • 22