Discuss the way that probability allows you, as an engineer, to more accurately predict and manage quality in processes and products. without these distributions, we might know that our defective rate is 15% and that the expected defects in a defective is 10. how would we manage quality if that's all we knew? alternatively, what do we know about the best case and worst case scenarios if we consider that the binomial distribution governs the number of defectives we'll see, and the poisson distribution governs the number of defects we'll see in a defective. how would you use this information to inform management about why sometimes we have good quality days, and other times we have bad quality days? how would you explain that sometimes we have lots of defects but very few defects per defective, while other times we have few defectives but each has lots of defects? how do the binomial and poisson distributions you understand what is happening in each scenario? use specific examples of probabilities in illustrating your explanations.