(4) Exponential smoothing with a smoothing constant equal to 0.15, assuming a March forecast of 15(000). (Round your intermediate forecast values and final answer to 2 decimal places.) Forecast thousands (5) A linear trend equation. (Round your intermediate calculations and final answer to 2 decimal places.) Yt thousands

14 Community General Hospital finds itself treating many bicycle accident victims. Data from the last seven 24-hour periods is shown below:   Day                  Bicycle Victims 1                                  8 2                                  14 3                                  8 4                                  14 5                                  18 6                                  15   With an alpha value of 0.31  and a starting forecast in day 3 equal to the 21 , what is the exponentially smoothed forecast for day 4?  (Round  to two decimal places)  15 What is the exponentially smoothed forecast for day 5?     (Round  to two decimal places)

(4) Exponential smoothing with a smoothing constant equal to 0.15, assuming a March forecast of 15(000). (Round your intermediate forecast values and final answer to 2 decimal places.) Forecast thousands (5) A linear trend equation. (Round your intermediate calculations and final answer to 2 decimal places.) Yt thousands

6. Consider the following data table. (12 Points) a) Forecast demand using exponential smoothing with an apha of 0.25, and an initial forecast of 128.0 for period 1. b) Calculate the MAD and MSE. Period Real demand 130 138 129 140 3 4 5 133

Use simple exponential smoothing with a=0.6 to forecast chargers sales for February through May. Assume that the forecast for January was 24 chargers. *** Month January Charger Sales 42 February 33 March 28 April 59 May ? a) What will be the forecast for May? b) Calculate the MSE.

Give typed explanation Part 2: Using exponential smoothing, the forecasted demand for period 5 using the smoothing constant determined in image= ?

Asvnch Problem - Statistical Forecasting Data Set – Eunice BC Fashion Monthly Sales, in million units. Year Total Sales Year Total Sales 2010 38 2016 43 2011 41 2017 40 2012 40 2018 45 2013 45 2019 47 2014 50 2020 42 2015 42 2021 48 Questions: a. Find the naïve forecast. b. Use the 3 years moving average forecast. c. Have a 5 years weighted moving average. d. Develop forecast using exponential smoothing with a = 0.2. e. Determine the trend line equation and present the forecast. f. Find the best forecast for year 2022. Note: Use the first 5 years as the training samples and the last 5 years as the forecasting samples. Solve it in Excel Sheet/Sheet with Equations as possible.

Given the following original forecast and actual data: Month Actual Forecast Jan 600 Feb 475 Mar 550 Apr 575 May 643 Jun 662 Jul ??? ??? Using a 2 month weighted moving average with weights of 75% for the previous month and 25% for two months back, what is the forecast for July. Round your answer to 1 decimal place. 400 -- —— ——

Amazon finds that sales in July are much greater relative to other months because of the Amazon Prime days in that month. Assuming that an exponential smoothing model is used for forecasting sales, what should the company best do to make the forecast for the next month (Aug) more reflective of reality? Please pick from the provided options.    F t+1 = αDt + (1-α) Ft     increase value of alpha     decrease value of alpha     stay with the same alpha     decrease the expected forecast for the current month (Ft)     On hearing our forecast, our clients probe - how sure are we about the forecast?  Which measure of errror (among those stated below) should we best use to respond?     a. Root MSE (RMSE)     b. Mean absolute percentage error (MAPE)     c. Mean forecast error (Avg. error)     d. Cumulative forecast error (CFE)

Given the following historical data, what is the simple three-period moving average forecast for period 6? Period 1 2 3 4 5 67.67 68.2 67.3 68.4 Value 73 66 64 73 66