As I understood— The null distribution is a theoretical distribution of test statistics that would be obtained if the null hypothesis were true. In other words, it represents the distribution of test statistics that would be expected by chance in the absence of any true effect or difference between groups. The null distribution can be calculated in different ways depending on the type of test being performed.
As each distributions i.e. t, χ2, F, have their own way of calculating statistic using tables, When we use software (e.g. R programming) to calculate p-value for them, Does the software convert respect distribution to Normal distribution for calculating the p-value?
Could someone explain the concept behind NULL distribution with a simulated example, (R program) if possible?
It is sometimes said that the p-value is uniformly distributed if the null hypothesis is true. So how come our alternative hypothesis normal distribution is compared to a uniform distribution? Am I missing a step in understanding this?