The chief of the emergency response services claims that their team responds to emergency distress calls within a 5 km radius in 360 seconds. An independent investigator wishes to test whether or not the presence of a thousand extra cars within the 5 km radius affects the emergency response time by 15.45 seconds. He randomly selects 100 distress calls and estimates the following regression: Ŷ₁ = 345 + 0.26X;, where ŷ, denotes the predicted response time measured in seconds for the ith emergency call and X; denotes the number of cars (in thousands) on the road within a 5 km radius at the time of the th emergency call. If ẞ₁ is the slope coefficient, which of the following options states the investigator's null and alternative hypotheses? ○ A. Hò: ß₁ >0.26 and H₁: ß₁ ≤0.26. B. Ho: B₁ =15.45 and H₁: B₁ #15.45. OC. Ho: B₁ =0.26 and H₁: B₁ #0.26. OD. Ho: B₁>15.45 and H₁: B₁ ≤15.45. Suppose act associated with the test the investigator wishes to conduct is 2.01. The p-value will be (Round your answer to three decimal places.) If the pre-specified significance level of the test was 5%, the calculated p-value suggests that we the null hypothesis.

The forecasting staff for the Prizer Corporation has developed a model to predict sales of its air-cushioned-ride snowmobiles. The model specifies that sales S vary jointly with disposable personal income Y and the population between ages 15 and 40, Z, and inversely with the price of the snowmobiles P. Based on past data, the best estimate of this relationship is S=kYZP where k has been estimated (with past data) to equal 100. If Y=11,000,Z=1,200, and P=20,000, what value would you predict for S? What happens if P is reduced to $17,500? How would you go about developing a value for k? What are the potential weaknesses of this model?

Estimate the double-log (log linear) time trend model for log cruise ship arrivals against log time. Estimate a linear time trend model of cruise ship arrivals against time. Calculate the root mean square error between the predicted and actual value of cruise ship arrivals. Is the root mean square error greater for the double log non-linear time trend model or for the linear time trend model?

Furniture Forecasting Futura Furniture Products manufactures upscale office furniture for the Office of the Future. The sales division comprises regionally based sales offices made up of sales representatives and regional managers. Sales representativeswho report to the regional managersconduct direct sales efforts with customers in their regions. As part of the sales process, representatives gather information about likely future orders and convey that information back to the regional managers. Regional managers use that information to create sales forecasts, which are then used as the basis for manufacturing schedules. Sales representatives and regional managers are both compensated on a salary plus commission (percentage of revenue as pricing is centrally controlled). However, a regional managers commission is adjusted based on regional sales that exceed the forecasted budget. Corporate managers are concerned with one of Futuras key products, the DeskPod. They worry that DeskPod forecasts are inaccurate, causing extreme havoc in the manufacturing process. How are the forecasts likely to be inaccurate? What do you think is driving this inaccuracy? How might this problem be solved?