I was a bit confused regarding the interpretation of
bptest in R (
library(lmtest)). The null hypothesis of
bptest is that the residuals have constant variance. So, a p-value less than 0.05 would mean that the homoscedasticity assumption would have to be rejected. However on this website:
I found the following results that confuse me:
data: lmMod BP = 3.2149, df = 1, p-value = 0.07297
A p-Value > 0.05 indicates that the null hypothesis(the variance is unchanging in the residual) can be rejected and therefore heterscedasticity exists. This can be confirmed by running a global validation of linear model assumptions (gvlma) on the lm object.
gvlma(lmMod) # validate if assumptions of linear regression holds true. # Call: gvlma(x = lmMod) Value p-value Decision Global Stat 15.801 0.003298 Assumptions NOT satisfied! Skewness 6.528 0.010621 Assumptions NOT satisfied! Kurtosis 1.661 0.197449 Assumptions acceptable. Link Function 2.329 0.126998 Assumptions acceptable. Heteroscedasticity 5.283 0.021530 Assumptions NOT satisfied!
So why is it the case that a p-value>0.05 means you have to reject the null hypothesis, when in fact a p-value less than 0.05 indicates that you have to reject the null hypothesis?