Interpret a multiple linear regression when Y is log transformed





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I have the following multiple linear regression model:
Log(y) = B0 + B1X1 + B2X2 + B3x3 + e.
X1 is a dummy that can take 0 = male and 1 = female and
X2 and X3 are continuous variables.



I am not entirely sure on how to interpret the coefficients for the variables.
The coefficient for the dummy variable is 0,20. Does that mean, that changing from male to female (male is baseline) the Y will increase by an average of 20%. Is it directly translated into percentage?



And for the continuous variables, the coefficient for X2 is 0,1. Does that mean that increasing X2 with 1 unit increases Y with an average of 10%? Again is it directly translated into percentage?



Sorry for this basic question, i was not, however, able to find a clear answer if it is directly translated into percentages or not.



All the best










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  • $begingroup$
    Possible duplicate of Interpretation of log transformed predictor
    $endgroup$
    – COOLSerdash
    13 mins ago


















1












$begingroup$


I have the following multiple linear regression model:
Log(y) = B0 + B1X1 + B2X2 + B3x3 + e.
X1 is a dummy that can take 0 = male and 1 = female and
X2 and X3 are continuous variables.



I am not entirely sure on how to interpret the coefficients for the variables.
The coefficient for the dummy variable is 0,20. Does that mean, that changing from male to female (male is baseline) the Y will increase by an average of 20%. Is it directly translated into percentage?



And for the continuous variables, the coefficient for X2 is 0,1. Does that mean that increasing X2 with 1 unit increases Y with an average of 10%? Again is it directly translated into percentage?



Sorry for this basic question, i was not, however, able to find a clear answer if it is directly translated into percentages or not.



All the best










share|cite|improve this question







New contributor




maS is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$












  • $begingroup$
    Possible duplicate of Interpretation of log transformed predictor
    $endgroup$
    – COOLSerdash
    13 mins ago














1












1








1





$begingroup$


I have the following multiple linear regression model:
Log(y) = B0 + B1X1 + B2X2 + B3x3 + e.
X1 is a dummy that can take 0 = male and 1 = female and
X2 and X3 are continuous variables.



I am not entirely sure on how to interpret the coefficients for the variables.
The coefficient for the dummy variable is 0,20. Does that mean, that changing from male to female (male is baseline) the Y will increase by an average of 20%. Is it directly translated into percentage?



And for the continuous variables, the coefficient for X2 is 0,1. Does that mean that increasing X2 with 1 unit increases Y with an average of 10%? Again is it directly translated into percentage?



Sorry for this basic question, i was not, however, able to find a clear answer if it is directly translated into percentages or not.



All the best










share|cite|improve this question







New contributor




maS is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$




I have the following multiple linear regression model:
Log(y) = B0 + B1X1 + B2X2 + B3x3 + e.
X1 is a dummy that can take 0 = male and 1 = female and
X2 and X3 are continuous variables.



I am not entirely sure on how to interpret the coefficients for the variables.
The coefficient for the dummy variable is 0,20. Does that mean, that changing from male to female (male is baseline) the Y will increase by an average of 20%. Is it directly translated into percentage?



And for the continuous variables, the coefficient for X2 is 0,1. Does that mean that increasing X2 with 1 unit increases Y with an average of 10%? Again is it directly translated into percentage?



Sorry for this basic question, i was not, however, able to find a clear answer if it is directly translated into percentages or not.



All the best







regression log






share|cite|improve this question







New contributor




maS is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|cite|improve this question







New contributor




maS is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|cite|improve this question




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Check out our Code of Conduct.









asked 1 hour ago









maSmaS

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New contributor





maS is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






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  • $begingroup$
    Possible duplicate of Interpretation of log transformed predictor
    $endgroup$
    – COOLSerdash
    13 mins ago


















  • $begingroup$
    Possible duplicate of Interpretation of log transformed predictor
    $endgroup$
    – COOLSerdash
    13 mins ago
















$begingroup$
Possible duplicate of Interpretation of log transformed predictor
$endgroup$
– COOLSerdash
13 mins ago




$begingroup$
Possible duplicate of Interpretation of log transformed predictor
$endgroup$
– COOLSerdash
13 mins ago










1 Answer
1






active

oldest

votes


















2












$begingroup$

Positive coefficients somehow indicate a positive effect, but they don't simply turn into percentages. There is a transformation. Let's say your model is $log y = b_0+b_1x_1$; this means $y=e^{b_0+b_1x_1}=A_0e^{b_1x_1}$. So, dummy or not, if $x_1$ increases by $1$ unit, $y$ increases by $e^{b_1}$, i.e. if $b_1=0.2$, $y$ increases by $e^{0.2}approx 1.22$, i.e. $22%$. The case is similar for your continuous variable.






share|cite|improve this answer









$endgroup$













  • $begingroup$
    I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
    $endgroup$
    – maS
    19 mins ago










  • $begingroup$
    Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
    $endgroup$
    – gunes
    17 mins ago














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1 Answer
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active

oldest

votes








1 Answer
1






active

oldest

votes









active

oldest

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active

oldest

votes









2












$begingroup$

Positive coefficients somehow indicate a positive effect, but they don't simply turn into percentages. There is a transformation. Let's say your model is $log y = b_0+b_1x_1$; this means $y=e^{b_0+b_1x_1}=A_0e^{b_1x_1}$. So, dummy or not, if $x_1$ increases by $1$ unit, $y$ increases by $e^{b_1}$, i.e. if $b_1=0.2$, $y$ increases by $e^{0.2}approx 1.22$, i.e. $22%$. The case is similar for your continuous variable.






share|cite|improve this answer









$endgroup$













  • $begingroup$
    I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
    $endgroup$
    – maS
    19 mins ago










  • $begingroup$
    Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
    $endgroup$
    – gunes
    17 mins ago


















2












$begingroup$

Positive coefficients somehow indicate a positive effect, but they don't simply turn into percentages. There is a transformation. Let's say your model is $log y = b_0+b_1x_1$; this means $y=e^{b_0+b_1x_1}=A_0e^{b_1x_1}$. So, dummy or not, if $x_1$ increases by $1$ unit, $y$ increases by $e^{b_1}$, i.e. if $b_1=0.2$, $y$ increases by $e^{0.2}approx 1.22$, i.e. $22%$. The case is similar for your continuous variable.






share|cite|improve this answer









$endgroup$













  • $begingroup$
    I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
    $endgroup$
    – maS
    19 mins ago










  • $begingroup$
    Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
    $endgroup$
    – gunes
    17 mins ago
















2












2








2





$begingroup$

Positive coefficients somehow indicate a positive effect, but they don't simply turn into percentages. There is a transformation. Let's say your model is $log y = b_0+b_1x_1$; this means $y=e^{b_0+b_1x_1}=A_0e^{b_1x_1}$. So, dummy or not, if $x_1$ increases by $1$ unit, $y$ increases by $e^{b_1}$, i.e. if $b_1=0.2$, $y$ increases by $e^{0.2}approx 1.22$, i.e. $22%$. The case is similar for your continuous variable.






share|cite|improve this answer









$endgroup$



Positive coefficients somehow indicate a positive effect, but they don't simply turn into percentages. There is a transformation. Let's say your model is $log y = b_0+b_1x_1$; this means $y=e^{b_0+b_1x_1}=A_0e^{b_1x_1}$. So, dummy or not, if $x_1$ increases by $1$ unit, $y$ increases by $e^{b_1}$, i.e. if $b_1=0.2$, $y$ increases by $e^{0.2}approx 1.22$, i.e. $22%$. The case is similar for your continuous variable.







share|cite|improve this answer












share|cite|improve this answer



share|cite|improve this answer










answered 44 mins ago









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  • $begingroup$
    I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
    $endgroup$
    – maS
    19 mins ago










  • $begingroup$
    Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
    $endgroup$
    – gunes
    17 mins ago




















  • $begingroup$
    I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
    $endgroup$
    – maS
    19 mins ago










  • $begingroup$
    Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
    $endgroup$
    – gunes
    17 mins ago


















$begingroup$
I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
$endgroup$
– maS
19 mins ago




$begingroup$
I have read that if the natural log is used it is approximately translated into a percentage change, if the change in x is small. Is that correct?
$endgroup$
– maS
19 mins ago












$begingroup$
Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
$endgroup$
– gunes
17 mins ago






$begingroup$
Yes, but approximate is the key term here, because Taylor expansion of $e^x$ is: $e^x=1+x+x^2/2!,...approx 1+x$ when $x$ is small. Which means $x%$ increase in something. Here, to execute this idea, your coefficients should be small.
$endgroup$
– gunes
17 mins ago












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