a) You estimate that the price elasticity of demand for clinic visits is -0.25. You anticipate that a major insurer will increase the co-payment from $20 to $25. This insurer covers 40,000 of your patients, and those patients' average 2.5 visits per year. What is your forecast of the change in the number of visits?

b) Because of fluctuations in insurance coverage, the average price paid out of pocket (P) by patients of an urgent care center varied, as the table shows. The number of visits per month (Q) also varied, and an analyst believes the two are related. The analyst also thinks the data show a trend. Runa regression of Q on P and Period to test these hypotheses. Then use the estimated parameters a,b, and c and the values of Month and P to predict Q (number of visits.) The prediction equation is Q = a + (b * Month) + (c *P).