Q+A Week 6

Hi,

In slide 13 about composite hypothesis, it is written that $p$ is the number of parameters in calculating $\hat{p}_i$.

In the example at slide 14, the null hypothesis is that the distribution is Poisson, and we want to estimate its parameter $\lambda$ using MLE. So to link that with slide 13, I guess that $\hat{p}_i = \frac{e^{-\hat{\lambda}\hat{\lambda}^{x_i}}{x_i !}$, is this correct? And what would be $p$ then?