What is the probability of potentially committing a Type II error (rejecting the null, which is that there is at least 64oz) if indeed the actual μ=63.8oz and not 64 oz as the company claims? Label your axes in both X and T-score. Label distribution (drawn based on company's claim with μ=64) as "old paradigm" and another distribution (drawn based on the actual μ=63.8) as "new paradigm". Label the centers for both distributions. Each distribution must have axes both in the units of X and Z or T-score.

necessary info: μ=64oz, n=40, x(bar)=63.7oz, Standard Dev.=2oz

I understand almost all of this... I just dont know how to find the probability of Beta (committing a Type 2 error)

If you need any other info let me know