Do you agree that all students in tertiary level (college, university, etc.) need to take at least one statistics subject in their program? Explain why.
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Do you agree that all students in tertiary level (college, university, etc.) need to take at least one statistics subject in their program? Explain why.
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- 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?A company manufacturers a product in the United States and sells it in England. The unit cost of manufacturing is 50. The current exchange rate (dollars per pound) is 1.221. The demand function, which indicates how many units the company can sell in England as a function of price (in pounds) is of the power type, with constant 27556759 and exponent 2.4. a. Develop a model for the companys profit (in dollars) as a function of the price it charges (in pounds). Then use a data table to find the profit-maximizing price to the nearest pound. b. If the exchange rate varies from its current value, does the profit-maximizing price increase or decrease? Does the maximum profit increase or decrease?You are considering a 10-year investment project. At present, the expected cash flow each year is 10,000. Suppose, however, that each years cash flow is normally distributed with mean equal to last years actual cash flow and standard deviation 1000. For example, suppose that the actual cash flow in year 1 is 12,000. Then year 2 cash flow is normal with mean 12,000 and standard deviation 1000. Also, at the end of year 1, your best guess is that each later years expected cash flow will be 12,000. a. Estimate the mean and standard deviation of the NPV of this project. Assume that cash flows are discounted at a rate of 10% per year. b. Now assume that the project has an abandonment option. At the end of each year you can abandon the project for the value given in the file P11_60.xlsx. For example, suppose that year 1 cash flow is 4000. Then at the end of year 1, you expect cash flow for each remaining year to be 4000. This has an NPV of less than 62,000, so you should abandon the project and collect 62,000 at the end of year 1. Estimate the mean and standard deviation of the project with the abandonment option. How much would you pay for the abandonment option? (Hint: You can abandon a project at most once. So in year 5, for example, you abandon only if the sum of future expected NPVs is less than the year 5 abandonment value and the project has not yet been abandoned. Also, once you abandon the project, the actual cash flows for future years are zero. So in this case the future cash flows after abandonment should be zero in your model.)
- Play Things is developing a new Lady Gaga doll. The company has made the following assumptions: The doll will sell for a random number of years from 1 to 10. Each of these 10 possibilities is equally likely. At the beginning of year 1, the potential market for the doll is two million. The potential market grows by an average of 4% per year. The company is 95% sure that the growth in the potential market during any year will be between 2.5% and 5.5%. It uses a normal distribution to model this. The company believes its share of the potential market during year 1 will be at worst 30%, most likely 50%, and at best 60%. It uses a triangular distribution to model this. The variable cost of producing a doll during year 1 has a triangular distribution with parameters 15, 17, and 20. The current selling price is 45. Each year, the variable cost of producing the doll will increase by an amount that is triangularly distributed with parameters 2.5%, 3%, and 3.5%. You can assume that once this change is generated, it will be the same for each year. You can also assume that the company will change its selling price by the same percentage each year. The fixed cost of developing the doll (which is incurred right away, at time 0) has a triangular distribution with parameters 5 million, 7.5 million, and 12 million. Right now there is one competitor in the market. During each year that begins with four or fewer competitors, there is a 25% chance that a new competitor will enter the market. Year t sales (for t 1) are determined as follows. Suppose that at the end of year t 1, n competitors are present (including Play Things). Then during year t, a fraction 0.9 0.1n of the company's loyal customers (last year's purchasers) will buy a doll from Play Things this year, and a fraction 0.2 0.04n of customers currently in the market ho did not purchase a doll last year will purchase a doll from Play Things this year. Adding these two provides the mean sales for this year. Then the actual sales this year is normally distributed with this mean and standard deviation equal to 7.5% of the mean. a. Use @RISK to estimate the expected NPV of this project. b. Use the percentiles in @ RISKs output to find an interval such that you are 95% certain that the companys actual NPV will be within this interval.practical example of the USES of Statistics, in business applications.Is formal training in statistics required to make use of BI tools? Why are we doing this?
- Suppose you were preparing two-way tables of percentages for the following pairs of variables. How would you run the percentages? Crime rate and unemployment rateUsing the data in the following table, calculate the return for investing in Boeing stock (BA) from January 2, 2008, to January 2, 2009, and also from January 3, 2011, to January 3, 2012, assuming all dividends are reinvested in the stock immediately. Historical Stock and Dividend Data for Boeing Date Price Dividend Date Price Dividend 1/2/2008 86.62 1/3/2011 66.40 2/6/2008 79.91 0.40 2/9/2011 72.63 0.42 5/7/2008 84.55 0.40 5/11/2011 79.08 0.42 8/6/2008 65.40 0.40 8/10/2011 57.41 0.42 11/5/2008 49.55 0.40 11/8/2011 66.65 0.42 1/2/2009 45.25 1/3/2012 74.22 Return from January 2, 2008, to January 2, 2009 is how much? (Round to two decimal places.)This type of analysis is most appropriate when the past is a good predictor of the future.
- Please help with correct answers in details: Step by step Suppose these data show the number of gallons of gasoline sold by a gasoline distributor in Bennington, Vermont, over the past 12 weeks. Week Sales (1,000sof gallons) 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 (a) Compute four-week and five-week moving averages for the time series. Week Time SeriesValue 4-WeekMovingAverageForecast 5-WeekMovingAverageForecast 1 17 2 21 3 20 4 24 5 18 6 17 7 21 8 19 9 22 10 21 11 16 12 22 b) Compute the MSE for the four-week moving average forecasts. (Round your answer to two decimal places.) c) Compute the MSE for the five-week moving average forecasts. (Round your answer to two decimal places.) d) What appears to be the best number of weeks of past data (three, four, or five) to use in the moving average computation? MSE for the three-week moving average is 9.65.…Sales for the past 12 months at computer success are given here: January 3,000 July 6,300 february 3,400 August 7,200 March 3,700 Sept 6,400 April 4,100 Oct 4,600 May 4,700 Nov 4,200 June 5,700 December 3,900 a. Use a 3-month moving average to forecast the sales for the months May through December b. Use a 4-month moving average to forecast the sales for the months May through December C. Compare the performance of the two methods by using the mean absolute deviation as the performance criterion. Which method would you recommend? d. Compare the performance of the two methods by using the mean absolute percent error as the performance criterion. Which method would you recommend? e. Compare the performance of the two methods by using the mean squared error as the performance criterion. Which method would you recommend?Paraphrase this one. Analyze and elaborate in 120 words. Time series analysis is used for non-stationary data—things that are constantly fluctuating over time or are affected by time. Industries like finance, retail, and economics frequently use time series analysis because currency and sales are always changing. Stock market analysis is an excellent example of time series analysis in action, especially with automated trading algorithms. Likewise, time series analysis is ideal for forecasting weather changes, helping meteorologists predict everything from tomorrow’s weather report to future years of climate change. Examples of time series analysis in action include: Weather data Rainfall measurements Temperature readings Heart rate monitoring (EKG) Brain monitoring (EEG) Quarterly sales Stock prices Automated stock trading Industry forecasts Interest rates