Use Holt’s double exponential smoothing with smoothing coefficients α=0.3, β=.15, S1=24.13 and G1=1.484 to calculate F1,2, G2 and S2.
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QUESTION 3
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A department store has recorded the sales of the best selling can opener model during the last 6 months. Observed values of the can opener sales are:
Period
1
2
3
4
5
6
Sales
25
22
26
33
28
30
Use Holt’s double exponential smoothing with smoothing coefficients α=0.3, β=.15, S1=24.13 and G1=1.484 to calculate F1,2, G2 and S2.
F1,2 =
S2 =
G2 =
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- QUESTION 2 The number of patients coming to the Healthy Start Maternity clinic has been increasing steadilyover the past eight months. You are provided with some historical data as follows: Month Clinic attendance (in thousands)1 3.42 3.93 4.54 5.05 5.86 5.97 6.58 6.7 a. Identify and give a brief explanation of the:-i. Dependent variableii. Independent variable b. Use simple linear regression to forecast annual demand for months 9 and 10 by using thetabular method to:-i. Derive the values for the intercept and slope. ii. Derive the linear regression equation. iii. Plot the linear regression line. iv. Develop a forecast of the clinic attendance for months 9 and 10.QUESTION 4 Suppose the following are the seasonal indices for the first three quarters of the year for a quarterly series: Quarter Seasonal Index Q1 72.4 Q2 85.3 Q3 109.6 Remember that the seasonal indices should average 100 so you should be able to infer the seasonal index for Q4. Furthermore, suppose that the estimated coeffcients from a regression of the deseasonalized series on Time are given below: Coefficients Intercept 2,506 Time 71.3 If the original value of the series in a Q1 was 2,040, then what is the seasonally adjusted value? (please round your answer to 1 decimal place)Question 1 Double Exponential Smoothing should be applied to time series with ____________________. Group of answer choices a. no trend and no seasonality. b. trend but no seasonality. c. seasonality but no trend. d. both trend and seasonality. Question 2 An analyst fits a Holt’s Double exponential smoothing model in StatTools to a time series data on sales with the smoothing parameters to be optimized by the software. In the output she notes that the optimized smoothing parameter for trend to be 0.0000. What does this imply? Group of answer choices a. There is no trend in the data. b. There is both trend and seasonality in the data. c. There could be trend in the data, but it is not smoothed over time by the model. d. This output does not make any sense!
- QUESTION 2:The manager of YTL Computers wants to develop next year’s quarterly forecasts of salesrevenue for its brand laptops. The sales are seasonal and the company believes that thefollowing most recent eight quarters of sales should be representative of next year’ssales: Year Quarter Sales (millions of dollars) 1 1 9.2 1 2 5.4 1 3 4.3 1 4 14.1 2 1 10.3 2 2 6.4 2 3 5.4 2 4 16.0 Determine the forecast of next year’s quarterly sales revenue for this line of laptops.Show all your workings.QUESTION 1The table below shows the sales figures for a brand of shoe over the last 12 months.Months SalesJanuary 69February 75March 86April 92May 95June 100July 108August 115September 125October 131November 140December 150 a. Using the following, forecast the sales for the months up to January the following year:- iii. Exponential Smoothing when α= .6 and the forecast for March is 350.QUESTION 2 In an effort to reduce energy costs, a major university has installed more efficient lights as well as automatic sensors that turn the lights off when no movement is present in a room. Historically, the cost of lighting an average classroom for 1 week has been $265. To determine whether the changes have signficantly reduced costs, the university takes a sample of 50 classrooms. They find that the average cost for 1 week is $247 with a standard deviation of $60. When testing the hypothesis (at the 5% level of significance) that the average energy use has decreased from the past, what is the test statistic? (please round your answer to 2 decimal places)
- Question 2Chad and James are two veteran sales executives who have been working for a well-established car distributor selling new cars. About six years ago, believing that there were good prospects in starting a business in selling used cars, both gentlemen left their employment to venture out.Since the beginning of their company, sales had been quite positive, but the owners now wanted to know more about future sales using an appropriate forecasting method. For a start, they wanted to focus on the quarterly sales of a popular brand of used cars.The sales figures over the last five years were used for the forecast. They are presented in the table below. (c) Explain why forecasting, despite its usefulness or sophistication, should only be considered a useful tool for decision making in any business. What are other factors that need to be considered? (d) The business of selling cars in Singapore, like many businesses, is subject to uncertainties.Discuss three (3) external factors,…Question 1. The table below shows the sales figure for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 a. Using the following, forecast the sales for the months up to january the following year:- i. A simple three month moving average ii. A three period weighted moving average using weights of 1, 2, and 3. Assign the highest weight to the most recent data iii. Exponential smothing when α = .6 and the forecast for march is 350 vi. Detemine which of the three forecasting technique is the most accurate using MAD N.B. Only answer IVQuestion 1. The table below shows the sales figure for a brand of shoe over the last 12 months. Months Sales January 69 February 75 March 86 April 92 May 95 June 100 July 108 August 115 September 125 October 131 November 140 December 150 a. Using the following, forecast the sales for the months up to january the following year:- i. A simple three month moving average ii. A three period weighted moving average using weights of 1, 2, and 3. Assign the highest weight to the most recent data iii. Exponential smothing when α = .6 and the forecast for march is 350
- Question 03 Suppose you sell stylish leather bags targeting young office going people who can use your bags to carry laptops and necessary stuff. You have already launched leather bags in February of this year and now based on the demand results of last 7 months, you want to predict the demand for your bags for the month of September. Hence, you want to select the right forecasting techniques and you are considering 2 period Moving Average, Naive technique and Exponential Smoothing (use any value between .10 - .15 as the value of alpha). Now figure out the better forecasting technique among 2 period Moving Average, Naive technique and Exponential Smoothing by doing the error calculation with the help of MAD, MSE, MAPE. Period Demand 2period Moving Average (Demand forecast) Naive technique (Demand forecast) Exponential Smoothing (Demand forecast) February 70 75 ** ** March 74 78 ** ** April 80 ** ** ** May 88 ** ** ** June…QUESTION 4 In an effort to reduce energy costs, a major university has installed more efficient lights as well as automatic sensors that turn the lights off when no movement is present in a room. Historically, the cost of lighting an average classroom for 1 week has been $265. To determine whether the changes have signficantly reduced costs, the university takes a sample of 50 classrooms. They find that the average cost for 1 week is $247 with a standard deviation of $60. When testing the hypothesis (at the 5% level of significance) that the average energy use has decreased from the past, what is your conclusion concerning the null hypothesis? Reject the null hypothesis Fail to reject the null hypothesisQuestion 1 Forecasting calculation X Month Sales (y)(000 units) 1 Feb. 19 2 Mar. 18 3 Apr. 15 4 May 20 5 Jun. 18 6 Jul. 22 7 Aug. 20 8 Sep a. Using a 5-month moving average, calculate September sales b. Calculate September sales Using a 3-month weighted moving average (weights are 0.60, 0.30. 0.10). c. Calculatate Exponential Smoothing (assume February sale is 19) sales in September (alpha 0.2, that means 1-0.2 = 0.8) d. Using regression analysis, what is Y (September sales) if X is 8? (use data> data analysis button> regression)