The computer manufacturer Skynet is relatively new in the industry. Their stated mission was the innovation of mobile computing for a better future. For the past 8 years they have been producing laptops, with the latest model the T-1000 released at the start of last year. Summary of Sales per model (in thousand $} 245 Skynet T-101 Skynet T-600 359 Skynet T-700 371 Skynet T-800 533 Skynet T-850 303 Skynet T-1000 218 What was the sales percentage for their latest model laptop? note: write the number with at most 2 decimat places without the unit (eg. 95.17 and NOT 95.17%)
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- At the beginning of each week, a machine is in one of four conditions: 1 = excellent; 2 = good; 3 = average; 4 = bad. The weekly revenue earned by a machine in state 1, 2, 3, or 4 is 100, 90, 50, or 10, respectively. After observing the condition of the machine at the beginning of the week, the company has the option, for a cost of 200, of instantaneously replacing the machine with an excellent machine. The quality of the machine deteriorates over time, as shown in the file P10 41.xlsx. Four maintenance policies are under consideration: Policy 1: Never replace a machine. Policy 2: Immediately replace a bad machine. Policy 3: Immediately replace a bad or average machine. Policy 4: Immediately replace a bad, average, or good machine. Simulate each of these policies for 50 weeks (using at least 250 iterations each) to determine the policy that maximizes expected weekly profit. Assume that the machine at the beginning of week 1 is excellent.The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
- In 1996, McDonald’s (MD) launched Campaign 55, reducing the prices ofits “flagship” sandwiches with the objective of regaining market share. Beforethe launch, suppose MD’s management envisioned two possible outcomes: astrong customer response or a weak response. Industry experts were notvery optimistic about the campaign. They assessed the probability of a strong response to be .40. MD predicted an expected profit of $50 million if theresponse proved to be strong. If the immediate customer response was weak,management believed that all was not lost. If MD could persuade themajority of its franchisees to back and help fund the campaign, the resultingprofit would be $20 million. However, if the majority rose up against thecampaign, the red ink would fly, and McDonald’s profit would be -$100million. MD considered these two outcomes to be equally likely.a. Given these assessments, construct a decision tree to determine MD’sexpected-profit-maximizing course of action.b. Suppose that MD has…The number of disk drives (in millions) made at a plant in China during the past 5 years follows: Year Disc drives 1 140 2 160 3 190 4 200 5 210 Forecast the number of disk drives to be made next year, using linear regressionMacomb Inc. used Excel to run a least-squares regression analysis on the production cost data resulting in the following output: Regression StatisticsMultiple R 0.9834 R Square 0.9596 Observations 30 Coefficients Standard Error T Stat P-ValueIntercept 174,980 61,580 2.84 0.021 Production units (X) 11.53 0.9265 12.44 0.000 What total cost would Macomb predict for a month in which production is 2,000 units? Multiple Choice $174,900 $63,433 $198,040 $23,037
- Jon is preparing a newsletter to his clients. As part of his newsletter, he reports their economic outlook for the coming year. He samples 85 of his clients, and they report that they expect to hire 7.8 new employees during the coming year. Last year all of his clients averaged 6.3 hires with a standard deviation of 4.0. Jon wants to know if the expected number of new hires has significantly increased at the 5% significance level. What are the null and alternate hypotheses?Using multiple regression, you have identified P12,000 of unit level costs for 3,000 units, P1,000 of product level costs for 40 products, and P3,500 of customer-level costs for ten customers. The cost of Job 002 which used 800 unit level activities, 4 product level activities, and one customer-level activities amounts to * A. P3,650 B. P3,250 C. P3,050 D. P2,950For the E-Commerce Retail Sales (Million$) data given in the table below, provide estimates from the 1st Quarter (Q1) of 2016 to the 3rd Quarter (Q3) of 2017 by using two models: 1) Single Exponential Smoothing with α=0.3 2) Moving Average with k=2. Calculate MAPE for each model. Quarter Year Actual Q1 2016 86802 Q2 2016 92004 Q3 2016 93795 Q4 2016 124651 Q1 2017 99491 Q2 2017 106590 Q3 2017 108291 Compare two models above (Single Exponential Smoothing and Moving Average) based on their accuracies. Which forecasting method appears to be better? Using the model you choose, provide forecast for the 4th Quarter (Q4) of 2017. Assuming that this model is overestimating, find the actual value of the Q4 of 2017 based on MAPE value. Some residual graphs from the first forecast model (including wider range of E-Commerce Retail Sales data) are given below. What do these graphs tell about the model? Explain each graph.
- Aqua Man Company manufactures and sells a single product. Planned and actual production in its first year of operation was 100,000 units. Planned and actual costs for the year were as follows: Manufacturing Non-manufacturing Variable P600,000 P500,000 Fixed P400,000 P300,000 The company sold 85,000 units of product at a selling price of P30 per unit. Using absorption costing, the company’s operating profit was Select one: a. P1,020,000 b. P975,000 c. P900,000 d. P750,000Calanute Beach Resort, a fictional seaside luxury hotelin Goa, India, had the following occupancy rates for 12months in 2014Month Occupancy Rate in %1 652 683 724 755 786 837 928 889 7610 6511 6412 69a Forecast the occupancy rate for January2015 usingsimple exponential smoothing with α = 0.4. Assumethat the forecast for Month 2 (F2) is 65%. b Forecast the January 2015 occupancy rate usingtrend-adjusted simple exponential smoothing with α =…All patients admitted to a particular hospital can be released on the same day or kept overnight forobservation. In a sample of 2550 patients, 1020 were kept overnight for observationa) What is the point estimate ?̂for the proportion of all patients kept overnight forobservation? [1]b) Construct a 99% confidence interval for the proportion of all patients kept overnight forobservation.
