I need help with these two problems. PLease shw all work so I can see steps.

10. (12 pts) The line of best fit, the regression line, is y = 0.0433x - 9.205, where x = year and y = average Boston temperature in degrees. (a) Use the regression line to estimate the average Boston temperature in 1890, to the nearest tenth of a degree. Show some work. (b) Use the regression line to predict the average Boston temperature in 2018, to the nearest tenth of a degree. Show some work. (c) What is the slope of the regression line? In a sentence, interpret what the slope is telling us, in the context of this real-world application. (d) In what year (to the nearest year) does the regression line predict an average Boston temperature of 60.0 degrees? Show work, solving an appropriate equation. 11. (20 pts) The cost, in dollars, for a company to produce x widgets is given by C(x) = 4000 + 4.00x for x 2 0, and the price-demand function, in dollars per widget, is p(x) = 30 - 0.02x for 0