Need help with answering below questions -

FRDBLEM 1 The Waco Tire Company (WTC) is considering expanding production to meet possible increases in demand. WTC's alternatives are to construct a new plant. expand the existing plant, or do nothing in the short run. It will cost them $1 million to build a new facility and $600,000 to expand their existing facility. The market for this particular product may expand. remain stable. or contract. ETC's marketing department estimates the probabilities of these market outcomes as 0.30. 0.50, and 0.20. respectively. The expected revenue for each alternative is presented in the table below. MK T expands MK T stable MK T contracts =0. 30 =0. 50 =0.20 Build new plant $1,450,000 $1,000,000 3350.000 Expand plant $1,100,000 $750,000 $350,000 Do nothing $0 $0 $0 a). Formulate a payoff table that species WTC's net payoff (in dollars] associated with each possible decision and each market condition in the future. b). Construct a decision tree to identify the course of action that maximizes WTC's expected profit.) (C). If you have a \"crystal ball" for sale which can tell the market outcome in advance, how much would you sell it to the WTC'xI PROBLEM 2 The station manager of a local television station is interested in predicting the amount of television (in hours)tl1et people will watch in the viewing area. The explanatory variables are: age (it years). education (highest level obtained. in years), and family slae (numberol family members In household). The multiple regression output from Excel is shown below. Summary measures Multiple R 0.8440 R-Squere 0.7123 Ad) R~5quare 0.6844 StErr of Estimate 0,5598 ANOVA Tabla Source dl' SS MS F p-velua | Explained 3 13.9682 4.6561 14.0564 0.0000 Unexplained 18 5.6413 0.3134 Regression coefcient: Coelcient Std Err 1.170 0.200 Family Size (x3) 3). Based on the estimation outputs, write clown the function form between the dependent variable and independent variables b). Interpret the result for each independent variable (i.e., Age, Education, Family Size). c). For a person of 30 years old, with MBA degree (Education=18 years), and from a family of 6 people, what is the predicted hours this person will watch the local television station based . n your estimation? d). If you are the station manager, what strategy will you take to increase your viewership based on your analysis? (Write only one strategy which you think is the best.) e). The manager also has data on each person's profession. They are: nancial manager, accountant, operations manager, and sales associate. The manager wants to study if their rofessions have any impact on theirTV watching behavior. A sample of data is shown in the table below. Using the sample data, show how the manager should operationalize the rofession data and enterthem into the regression? f) Suppose we hypothesize that the impact of age on the amount of TV people watch depends on their education levels. Please describe how you would operationallze and test this idea sing a linear regression. No need to explicitly write out the hypothesis like we did in class, just describe how you would test it using a linear regression