Can normality test be used to estimate accuracy of regression model outputs?
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I have recently received reviews for one of the research papers I have written. One of the reviewers wrote the following as a suggestion:
"Before using Pearson correlation coefficient, suggesting add normality test for regression model outputs and the simulated values."
The research involves building a regression model and comparing it's outputs with that of software generated outputs. Pearson correlation coefficient/Coefficient of Determination (R2) is calculated as a performance metric for this model. According to Wikipedia, normality tests are used to determine if a data set is well-modeled by a normal distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed.
Can you please help me understand what the reviewer meant by saying "add normality test for regression model outputs and the simulated values"
Any help would be greatly appreciated.
statistics normal-distribution machine-learning
edited Dec 18 '18 at 10:34
Math Girl
633318
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
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add a comment |
$begingroup$
I have recently received reviews for one of the research papers I have written. One of the reviewers wrote the following as a suggestion:
"Before using Pearson correlation coefficient, suggesting add normality test for regression model outputs and the simulated values."
The research involves building a regression model and comparing it's outputs with that of software generated outputs. Pearson correlation coefficient/Coefficient of Determination (R2) is calculated as a performance metric for this model. According to Wikipedia, normality tests are used to determine if a data set is well-modeled by a normal distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed.
Can you please help me understand what the reviewer meant by saying "add normality test for regression model outputs and the simulated values"
Any help would be greatly appreciated.
statistics normal-distribution machine-learning
edited Dec 18 '18 at 10:34
Math Girl
633318
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
$endgroup$
add a comment |
$begingroup$
I have recently received reviews for one of the research papers I have written. One of the reviewers wrote the following as a suggestion:
"Before using Pearson correlation coefficient, suggesting add normality test for regression model outputs and the simulated values."
The research involves building a regression model and comparing it's outputs with that of software generated outputs. Pearson correlation coefficient/Coefficient of Determination (R2) is calculated as a performance metric for this model. According to Wikipedia, normality tests are used to determine if a data set is well-modeled by a normal distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed.
Can you please help me understand what the reviewer meant by saying "add normality test for regression model outputs and the simulated values"
Any help would be greatly appreciated.
statistics normal-distribution machine-learning
edited Dec 18 '18 at 10:34
Math Girl
633318
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
$endgroup$
I have recently received reviews for one of the research papers I have written. One of the reviewers wrote the following as a suggestion:
"Before using Pearson correlation coefficient, suggesting add normality test for regression model outputs and the simulated values."
The research involves building a regression model and comparing it's outputs with that of software generated outputs. Pearson correlation coefficient/Coefficient of Determination (R2) is calculated as a performance metric for this model. According to Wikipedia, normality tests are used to determine if a data set is well-modeled by a normal distribution and to compute how likely it is for a random variable underlying the data set to be normally distributed.
Can you please help me understand what the reviewer meant by saying "add normality test for regression model outputs and the simulated values"
Any help would be greatly appreciated.
statistics normal-distribution machine-learning
statistics normal-distribution machine-learning
edited Dec 18 '18 at 10:34
Math Girl
633318
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
edited Dec 18 '18 at 10:34
Math Girl
633318
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
edited Dec 18 '18 at 10:34
Math Girl
633318
edited Dec 18 '18 at 10:34
Math Girl
633318
edited Dec 18 '18 at 10:34
Math Girl
633318
633318
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
asked Dec 14 '18 at 10:34
ash_0605ash_0605
12
12
add a comment |
add a comment |
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