data: https://docs.google.com/spreadsheets/d/1JxdZfy86CwJds_AWY-LBDWdh3s1DVS4VSWIrAUmPoLg/edit?usp=sharing
please help with both questions and I'll give a thumbs-up, and answers have to be correct, thanks!
(i) With 95% confidence, find the average cost of flying a commercial flight using Boeing 737s when the number of passengers is 70. Lower Bound = 5.376 (use three decimals in your answer) Upper Bound = 5.774 (use three decimals in your answer)(k) Last month, the TSE lndex's monthly rate of return was 1.5%. This is, at the end of last month the value of the TSE Index was 1.5% higher than at the beginning of last month. With 95% condence, find the last month's rate of return on Acme Oil and Gas stock. Lower Bound = o_127 555 (use three decimals in your answer) Upper Bound = 1_315 it! (use three decimals in your answer) (1 point) The Capital Asset Price Model (CAPM) is afinancial model that attempts to predict the rate of return on a nancial instrument, such as a common stock, in such a way that it is linearly related to the rate of return on the overal market. Specifically, RSIuckAJ = .80 + lRMarkeu + e;- You are to study the relationship between the two variables and estimate the above model: RSIuckAJ - rate of return on StockAfor month i, i = l, 2, , 59. RMarketJ - market rate of return for month i, i = 1, 2, , 59. 31 represents the stocks 'beta' value, or its systematic risk. It measure's the stocks volatility related to the market volatility. 50 represents the risk-free interest rate. The data in the .csv file contains the data on the rate of return of a large energy company which will be referred to as Acme Oil and Gas and the corresponding rate of return on the Toronto Composite Index (T SE) for 59 randomly selected months. Therefore RAng represents the monthly rate of return for a common share of Acme Oil and Gas stock; RTSEJ represents the monthly rate of return (increase or decrease) of the TSE Index for the same month, month 1'. The rst column in this data le contains the monthly rate of return on Acme Oil and gas stock; the second column contains the monthly rate of return on the TSE index for the same month. (1 point) Can the cost of flying a commercial airliner be predicted using regression analysis? If so, what variables are related to this cost? A few of many variables that can potentially contribute are type of plane, distance, number of passengers, amount of luggagelfreight, weather condition, direction of destination, or even pilot skill. Suppose a study is conducted using only Boeing 737s traveling 800 km on comparable routes during the same season of the year. Can the number of passengers predict the cost of ying such routes? It seems logical that more passengers result in more mass and more baggage, which could, in turn, result in increased fuel consumption and other costs. Suppose the data displayed below are the cost and associated number of passengers for thirtysix BOOkm commercial airline ights using Boeing 7375 during the same season of the year. We will use these data to develop a regression model to predict cost by number of passengers. The data in the .csv file contains the data on the cost and number of passengers of 36 observations
