In lecture on Friday 3 December (beginning at minute 36) and Monday 6 December, you were introduce to the concept of "interval estimates": attempts to estimate unknown values of parameters by specifying bounded ranges (i.e. intervals) of plausible values for these parameters, using information from data we have observed. We focused primarily on confidence interval estimates, which were also covered in Chapter 21 and in your quiz section exercise on Tuesday 7 December. At the end of lecture on Monday 6 December, we also briefly examined another kind of interval estimate known as a credible* interval. One big difference between confidence intervals and credible intervals is that confidence intervals are based on confidence levels, while credible intervals are based on coverage probabilities. Confidence levels are often misinterpreted to be coverage probabilities. For this participation report, to the best of your ability, answer each of the two questions (approximately one to two sentences for each question). 1. Why are confidence levels useful? In other words, what do they allow us to do when we are trying to calculate confidence intervals? A confidence level is a probability, but what kind of probability is it? Is it (a) the probability of observing a specific range of possible outcomes assuming a particular value of a parameter, or (b) the probability of a specific value of a parameter assuming the outcome we have actually observed? Why do you think this