After graduation, you take a position at Top-Slice, a well-known manufacturer of golf balls. One of your duties is to forecast monthly demand for goif balls, Using the following data, you derveloped a regression model that expresses monthly sales as a function of average temperature for the month: Monthly sales =964.7+100.3( average temperature ) Click the icon to view the additional data. a. Show how the a^ and b^ values of -964.7 and 100.3 were calculated. Calculate the slope coefficient, b^ (enter your responses as whole numbers). b^=12()212(733)()=100.3 Calculate the intercept term, a (enter your responses rounded to one decimal place). a^=100.3x=964.7 b. Use the regression forecasting model to forecast total golf ball sales for June and July 2018. Average temperatures are expected to be 79 degrees in June and 86 degrees in July. The forecast of total golf ball sales for June 2018 is (Enter your response rounded to the nearest whole number.) The forecast of total golf ball sales for July 2018 is ( Enter your response rounded to the nearest whole number.) c. Is this regression model a time series or a causal forecasting model? A. This regression model is a causal forecasting model because both the chronology of the observations and their values affect the number of golf balls. B. This regression model is a causal forecasting model because the number of golf balls to be sold each month depends on the expected average temperature for the month. C. This regression model is a time series forecasting model because the number of golf balls to be sold each month depends only on the time period. D. This regression model is a a time series forecasting model because time series are used to develop forecasts