Are the independent variables in the linear regression independent?
$begingroup$
Ask some statistical concepts of linear regression:
Does the general linear regression specify that the independent variables are independent of each other?
I have seen a similar description that needs to match the characteristics of LINE
I also saw that some people say no, only when collinearity appears.
Next, how do you prove the dependent/independent relationship between "independent variables"? Is it a method of using correlation coefficients or probability independent events?
regression
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
$endgroup$
add a comment |
$begingroup$
Ask some statistical concepts of linear regression:
Does the general linear regression specify that the independent variables are independent of each other?
I have seen a similar description that needs to match the characteristics of LINE
I also saw that some people say no, only when collinearity appears.
Next, how do you prove the dependent/independent relationship between "independent variables"? Is it a method of using correlation coefficients or probability independent events?
regression
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
$endgroup$
add a comment |
$begingroup$
Ask some statistical concepts of linear regression:
Does the general linear regression specify that the independent variables are independent of each other?
I have seen a similar description that needs to match the characteristics of LINE
I also saw that some people say no, only when collinearity appears.
Next, how do you prove the dependent/independent relationship between "independent variables"? Is it a method of using correlation coefficients or probability independent events?
regression
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
$endgroup$
Ask some statistical concepts of linear regression:
Does the general linear regression specify that the independent variables are independent of each other?
I have seen a similar description that needs to match the characteristics of LINE
I also saw that some people say no, only when collinearity appears.
Next, how do you prove the dependent/independent relationship between "independent variables"? Is it a method of using correlation coefficients or probability independent events?
regression
regression
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
asked Feb 26 at 3:15
WeiYuanWeiYuan
28317
28317
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
$begingroup$
The use of the name "independent variable" is unfortunately misleading. Personally I prefer to use other terms if I can. They are not assumed to be independent of each other.
In the regression model you condition on them so their dependence is generally not material to prediction, but there is a possible issue with estimation of individual effects/effect sizes (particularly in relation to deciding which variables are important, for example).
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
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add a comment |
$begingroup$
It is not assumed that the "explicative variables" must be independent from each other. However, we must be aware of the problem of colinearity.
If your explicative variables are correlated, then the model may get confused about which one of them is having the effect on the "target". It's true that correlation and dependency are two different concepts, but this is still an idea to keep in mind
answered Feb 26 at 7:24
asdfasdf
1873
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add a comment |
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2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
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active
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active
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$begingroup$
The use of the name "independent variable" is unfortunately misleading. Personally I prefer to use other terms if I can. They are not assumed to be independent of each other.
In the regression model you condition on them so their dependence is generally not material to prediction, but there is a possible issue with estimation of individual effects/effect sizes (particularly in relation to deciding which variables are important, for example).
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
$endgroup$
add a comment |
$begingroup$
The use of the name "independent variable" is unfortunately misleading. Personally I prefer to use other terms if I can. They are not assumed to be independent of each other.
In the regression model you condition on them so their dependence is generally not material to prediction, but there is a possible issue with estimation of individual effects/effect sizes (particularly in relation to deciding which variables are important, for example).
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
$endgroup$
add a comment |
$begingroup$
The use of the name "independent variable" is unfortunately misleading. Personally I prefer to use other terms if I can. They are not assumed to be independent of each other.
In the regression model you condition on them so their dependence is generally not material to prediction, but there is a possible issue with estimation of individual effects/effect sizes (particularly in relation to deciding which variables are important, for example).
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
$endgroup$
The use of the name "independent variable" is unfortunately misleading. Personally I prefer to use other terms if I can. They are not assumed to be independent of each other.
In the regression model you condition on them so their dependence is generally not material to prediction, but there is a possible issue with estimation of individual effects/effect sizes (particularly in relation to deciding which variables are important, for example).
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
answered Feb 26 at 5:09
Glen_b♦Glen_b
213k22411760
213k22411760
add a comment |
add a comment |
$begingroup$
It is not assumed that the "explicative variables" must be independent from each other. However, we must be aware of the problem of colinearity.
If your explicative variables are correlated, then the model may get confused about which one of them is having the effect on the "target". It's true that correlation and dependency are two different concepts, but this is still an idea to keep in mind
answered Feb 26 at 7:24
asdfasdf
1873
$endgroup$
add a comment |
$begingroup$
It is not assumed that the "explicative variables" must be independent from each other. However, we must be aware of the problem of colinearity.
If your explicative variables are correlated, then the model may get confused about which one of them is having the effect on the "target". It's true that correlation and dependency are two different concepts, but this is still an idea to keep in mind
answered Feb 26 at 7:24
asdfasdf
1873
$endgroup$
add a comment |
$begingroup$
It is not assumed that the "explicative variables" must be independent from each other. However, we must be aware of the problem of colinearity.
If your explicative variables are correlated, then the model may get confused about which one of them is having the effect on the "target". It's true that correlation and dependency are two different concepts, but this is still an idea to keep in mind
answered Feb 26 at 7:24
asdfasdf
1873
$endgroup$
It is not assumed that the "explicative variables" must be independent from each other. However, we must be aware of the problem of colinearity.
If your explicative variables are correlated, then the model may get confused about which one of them is having the effect on the "target". It's true that correlation and dependency are two different concepts, but this is still an idea to keep in mind
answered Feb 26 at 7:24
asdfasdf
1873
answered Feb 26 at 7:24
asdfasdf
1873
answered Feb 26 at 7:24
asdfasdf
1873
answered Feb 26 at 7:24
asdfasdf
1873
1873
add a comment |
add a comment |
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