Dear All,
I would like to test the simple linear regression model only x and y values.
Could I use R-square and ANOVA F-test to exam the model?
And could I set following rating the Four scenarios of R-square and F-test(p-value)?
1) high R-square and low p-value
means your model explains a lot of variation within the data and is significant (best scenario)
2) low R-square and low p-value (p-value <= 0.05)
means that your model doesn't explain much of variation of the data but it is significant (better than not having a model)
3) high R-square and high p-value
means that your model explains a lot of variation within the data but is not significant (model is worthless)
4) low R-square and high p-value (p-value > 0.05)
means that your model doesn't explain much of variation of the data and it is not significant (worst scenario)
Thanks
Wilson
I would like to test the simple linear regression model only x and y values.
Could I use R-square and ANOVA F-test to exam the model?
And could I set following rating the Four scenarios of R-square and F-test(p-value)?
1) high R-square and low p-value
means your model explains a lot of variation within the data and is significant (best scenario)
2) low R-square and low p-value (p-value <= 0.05)
means that your model doesn't explain much of variation of the data but it is significant (better than not having a model)
3) high R-square and high p-value
means that your model explains a lot of variation within the data but is not significant (model is worthless)
4) low R-square and high p-value (p-value > 0.05)
means that your model doesn't explain much of variation of the data and it is not significant (worst scenario)
Thanks
Wilson