Suppose we have the following time series data on variable Y (where t = trend): t Y 1 100 2 120 3 160 4 200 Using simple exponential smoothing where a = t = 5. Report your answer to only one decimal point. 0.5, calculate the forecast of Y when
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- Use simple exponential smoothing with a = 0.6 to forecast the tire sales for September through December. Assume that the forecast for August was for 46 sets of tires. Do your forecasts seem to be biased? Why or why not? Month Sales August 53 September35 October 48 November 40Use simple exponential smoothing with a = 0.3 to forecast bike sales for September through December. Assume that the forecast for September was 60 units. a) What will be the forecast for December? b) Calculate the MAD. Last saved 11:13:58 AM budy Questions Filter (25) Month September October November December F3 X C O Search P Bike Sales 54 72 60 ? YQuestion 3 The number of tons of brake assemblies received at an auto parts distribution center last month was 625. The forecast tonnage was 650 for last month. The company uses a simple exponential smoothing model with a smoothing constant of 0.46 to develop its forecasts. What will be the company's forecast for the next month? Add your answer
- Campus Advising needs to allocate time this week for office appointments, so she needs te forecast the number of students who will seek appointments. The advisor has gathered th following time series data recently: Period Student Appointments 4 weeks ago 95 3 weeks ago 80 2 weeks ago 65 Last week 50 Answer the next two questions (questions 11 and 12), based on this information. 11. What is this week's forecast for student appointments using a three-week moving average? a) 80 b) 50 c) 52 d) 65 e) 78Consider the following time series data: Month 1 2 3 4 5 6 7 Value 24 13 20 12 19 23 15 Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8? Compute MSE using the average of all the data available as the forecast for the next period. What is the forecast for month 8? Which method appears to provide the better forecast?Define Forecasts and forecast errors in time series anaylsis?
- (Ch7) If the mean time between in-flight aircraft engine shutdowns is 12,500 operating hours, what is the 90 percentile on the distribution of the number of hours until the next shutdown? (hint: convert the mean time between events to the mean events per hour λ, then apply inverse exponential) Question 7Select one: a. 20,180 hours b. 18,724 hours c. 23,733 hours d. 28,782 hoursUse properties of logarithms to expand the logarithmic expression as much as possible. Where possible, evaluate logarithmic expressions without using a calculator. log 10,000Director Very Busy needs to allocate time this week for office appointments, so he needs to forecast the number of employees who will seek appointments. The director has gathered the following time series data recently Period Employee Appointments 4 weeks ago 95 3 weeks ago 80 2 week ago 65 last week 50
- Consider the following time series. 1 2 4 Y, 6 11 9 14 15 a. Choose the correct time series plot. (i) 16 (ii) 16 14 14 12 12 10 10 8 6. 6. 4 4 2 1 Time Period (t) Time Period (t) Time Period () Time Period (t) (iii) 16 (iv) 16 14 14 12 12 10 10 8 1 Time Period (t) Time Period (t) Time Series Value Time Series Value Time Series Value Time Series ValueDo not use software on this question. Use pencil, paper, and your calculator to calculate the values of both the mean and the median for this sample data. Here are the snowfall amounts for 12 more-than-a-trace snowfalls for this February 2020 and March 2020 (rounded to the nearest inch): 4 0 6 6 0 6 0 9 2 3 1 2 Using just the values for the median and the mean, is the distribution symmetric or skewed? If skewed, which direction? A. Skewed left since mean < median B. Symmetric since mean is about the same as the median C. Skewed left since mean > median D. Skewed right since mean < median E. Skewed right since mean > medianEconomics You own a restaurant near the beach. Business has been growing each year, but obviously spikes during the summer months. A regression produces the following equation: M = 30,000 + 500t + 1,000S Where M is monthly sales, t is years past 2010, and S is a dummy variable for the summer months. If the month is June, July, or August, insert a "1". If not, the value for S is zero. What are the predicted sales for July 2020? Enter as a value.