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Glen_b
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I am reading a paper and come across the following information:

 Predictor    Dependent Variable    Square R Square    Beta    P
     A                D                .12      .35   <0.05
     B                D                .16      .40   <0.05
     C                D                .13      .36   <0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?

I am reading a paper and come across the following information:

 Predictor    Dependent Variable    Square R    Beta    P
     A                D                .12      .35   <0.05
     B                D                .16      .40   <0.05
     C                D                .13      .36   <0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?

I am reading a paper and come across the following information:

 Predictor    Dependent Variable    R Square    Beta    P
     A                D                .12      .35   <0.05
     B                D                .16      .40   <0.05
     C                D                .13      .36   <0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?

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Glen_b
  • 290.5k
  • 37
  • 652
  • 1.1k

I am reading a paper and come across the following datainformation:

Predicator//Dependent Variable//Square R//Beta//P

A//D//.12//.35//<0.05

B//D//.16//.40//<0.05

C//D//.13//.36//<0.05

 Predictor    Dependent Variable    Square R    Beta    P
     A                D                .12      .35   <0.05
     B                D                .16      .40   <0.05
     C                D                .13      .36   <0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?

I am reading a paper and come across the following data:

Predicator//Dependent Variable//Square R//Beta//P

A//D//.12//.35//<0.05

B//D//.16//.40//<0.05

C//D//.13//.36//<0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?

I am reading a paper and come across the following information:

 Predictor    Dependent Variable    Square R    Beta    P
     A                D                .12      .35   <0.05
     B                D                .16      .40   <0.05
     C                D                .13      .36   <0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?

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linear regression

I am reading a paper and come across the following data:

Predicator//Dependent Variable//Square R//Beta//P

A//D//.12//.35//<0.05

B//D//.16//.40//<0.05

C//D//.13//.36//<0.05

Authors are using linear regression to compute the correlation between A and D, B and D and C and D, and they claim there is significant positive correlations between each and every one of them. I am confused and do not understand how can the authors draw such a conclusion with the presented data?