The following is the data regarding sale of woodstoves in the last 3 years. Season Summer Year Spring Fall Winter 2010 18 10 26 42 2011 26 18 34 50 2012 34 29 42 58 What is the seasonal relative for the summer ? (Please keep 3 decimal places for your answer)
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What is the seasonal relative for the summer? (Please keep 3 decimal places for your answer)
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- The file P13_42.xlsx contains monthly data on consumer revolving credit (in millions of dollars) through credit unions. a. Use these data to forecast consumer revolving credit through credit unions for the next 12 months. Do it in two ways. First, fit an exponential trend to the series. Second, use Holts method with optimized smoothing constants. b. Which of these two methods appears to provide the best forecasts? Answer by comparing their MAPE values.q1(a)Imagine that you need to introduce a new gadget such as the Apple Watch. Determine which forecasting method is appropriate for projecting the future demand of such this gadget. b)ARIMA is mostly used to forecast future values using historical time series data, as we all know. Its primary use is in short-term forecasting with at least 38-40 historical data points and a small number of outliers. If we don't have at least 38 data points, we should consider using another strategy.V. Let's Explore / Let's Create 1. Discuss the other types of forecasting methods that financial analysts use to predict future revenues. 2. Are there any several other factors that may need to be considered that affects the sales forecast? RUBRIC Criteria Poor (3 Points) Fair (7 Points) Fair Good (10 Points) Good Deer
- It wouldnt let me take a screenshot of the table so I had to copy and paste it in here. My question is: How do you Calculate a moving average forecast using the last 2 and 4 dates of stay. What is the prediction for 7/1/2021 for each technique? Discussion Question 1 - 200 room hotel Forecasts MA 2 Errors MA 4 Errors ES (0.8) Errors ES (0.5) Errors Date Day of Week Rooms Sold MA 2 MA 4 ES (0.8) ES (0.5) AE APE AE APE AE APE AE APE 6/1/2021 Tuesday 123 6/2/2021 Wednesday 109 6/3/2021 Thursday 140 6/4/2021 Friday 199 6/5/2021 Saturday 179 6/6/2021 Sunday 140 6/7/2021 Monday 117 6/8/2021 Tuesday 132 6/9/2021 Wednesday 108 6/10/2021 Thursday 151…Font Paragraph Styles Question 3 Consider the following from an estate agent's business nationally: Month Houses Sold Jan Feb Mar 380 360 390 Apr May June July Aug Sep Oct 400 390 380 394 454 460 460 Nov Dec 430 370 a) Calculate the three point moving averages (quarters) and seasonal variation for the above data b) Define moving averages and how they're useful in forecasting (use Harvard referencing) c) At races, your horse, White Rum, has a probability of 1/20 of coming 1st, 1/10 of coming 2nd and a probability of 4 in coming 3rd. First place pays $5,000 to the winner, second place $4,000 and third place $1,350. Hence, is it worth entering the race if it costs $1050?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 3 An organization uses a business intelligence system to predict products that tend to be purchased together. This is an example of. O A) Regression Analysis B) Cluster Analysis C) REM Analysis D) Market Basket AnalysisQuestion content area Part 1 Sales of Volkswagen's popular Beetle have grown steadily at auto dealerships in Nevada during the past 5 years (see table below). Year Sales 1 450 2 510 3 516 4 555 5 575 Part 2 a) Forecasted sales for year 6 using the trend projection (linear regression) method are enter your response here sales (round your response to one decimal place). Part 3 b) The MAD for a linear regression forecast is enter your response here sales (round your response to one decimal place). Part 4 c) The MSE for the linear regression forecast is enter your response here sales (round your response to one decimal place).Tools View Week 3 Bonus Activity- DEMAND FORECASTING CASE STUDY After reviewing the forecasting demonstration and looking over the slides, complete the following case activity and transfer your answers to the appropriate questions in the Canvas activity quiz. You have been hired as a demand planning intern for Hawaiian Island Creations (HIC). They want you to de- velop a forecast for their HIC Papanui style of sun- glasses. The goal is to determine how many pair they will produce to meet retailer demand in July 2021. During your first meeting, you were handed some data to work with and the product team talked about the company's upcoming promotional blitz to support Summer Break '21 in major vacation destinations. Month Forecast Demand January 2021 4.000 3,300 February 2021 4,200 3,900 March 2021 4,500 4,300 April 2021 4.800 4,200 May 2021 5 000 5.400 of 4 P Type here to search 立
- Q3) Discuss Qualitative forecasting technique. Explain the situations where we use Qualitative methods. Discuss Delphi forecasting method and its challenge.st Info Period 1 2 3 4 5 6 7 8 9 10 K Develop two exponential smoothing forecasts for periods 2 through 11. For the first forecast, use a = 0.3. For the second, use α = 0.7. Assume that your forecast for period 1 was 205. Click the icon to view the time series data. Find the exponential smoothing forecast for each period when a = 0.3 (enter your responses rounded to one decimal place). Demand 222 249 222 228 235 155 161 153 163 152 X Period 1 2 Demand 222 249 Forecast (α = 0.3) 205If ABC Corporation has following historical data about sales volume: Years Sales Years Sales Years Sales Years Sales 2001 110 2006 99 2011 100 2016 110 2002 112 2007 101 2012 104 2017 111 2003 122 2008 95 2013 108 2018 109 2004 111 2009 98 2014 102 2019 114 2005 104 2010 96 2015 115 2020 112 Note: All the sale values are in thousands. Required: Which type of forecasting approach is suitable for this type of data? Which forecasting technique is best to employ in order to forecast the above data? And also define the suggested technique. Calculate the predicted values by employing the discussed technique in part (b) on the above data.