for the 8th week using weights of 3, 2, and 1 (where the most recent week receives the highest weight). (Round all forecasts to the nearest whole unit.) b. Calculate the MAD for this forecast. What does the MAD indicate? he number of students enrolled in Spring Valley Elementary school has been steadily acreasing over the past five years. The School Board would like to forecast enrolment or years 6 and 7 in order to better plan capacity. The past five years enrolment is dicated in table 3:
Q: Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend,…
A: Delphi Technique of forecasting would be appropriate to predict the demand for vacations on the…
Q: It has been said that forecasting using exponential smoothing is like driving a car by looking in…
A: A person drives a car, he knows where he has to look. In most of the time, he has to look straight…
Q: A manager of a store that sells and installs spas wants to prepare a forecast for January, February,…
A: The trend equation for monthly demand: Ft = 70 + 5t Where t = 0 in June of last year. In this…
Q: Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17…
A: The concept used here is forecasting with Moving averages and forecast evaluation using MAE, MSE and…
Q: Week Actual Forecast Demand 1 52 48 2 42 46 3 56 52 4 45 47 true or false Assume that the actual…
A: The table shows the calculation of forecast of demand using the simple moving average method with 3…
Q: What is the forecast using exponential smoothing with alpha = .6? 2. If we decide to…
A: ANSWER IS AS FOLLOWS:
Q: The actual number of patients at Omaha Emergency Medical Clinic for the first sIX weeks of this year…
A: This problem can be solved using the weighted moving average method of forecasting.
Q: The table below shows the demand for a particular brand of microwave oven in a department store.…
A: Given-
Q: The demand for Krispee Crunchies, a favorite breakfast cereal of people born in the 1940s, is…
A:
Q: Sales of tablet computers at Ted Glickman's electronics store in Washington, D.C., over the past 10…
A: Exponential Smoothing is a hugely familiar system to provide a smoothed time series. In the single…
Q: Period Actual 1 12 2 15 16 4 16 Given the information in the following table, Use exponential…
A: Note: - Since the actual data for period 5 is not given, the trend-adjusted forecast can be made by…
Q: The Yummy Ice Cream Company uses the exponential smoothing method. Last week the forecast was…
A:
Q: The following table contains the demand from the last 10 months. Calculate the single exponential…
A: The general formula of exponential smoothing: forecast = actual demand of previous period…
Q: DEMAND FORECAST WITH LINEAR REGRESSION Historical demand for a product is: Period MONTH DEMAND x2 XY…
A: Period (x) Month Demand (y) 1 January 12 2 February 11 3 March 15 4 April 12 5 May 16 6…
Q: You discovered that the forecasting error falls beyond the acceptable ranges in the past three…
A: Find the given details below: Given details: Period Actual Forecast (A-F) Error (A) (F)…
Q: The following table contains the demand from the last 10 months. Calculate the exponential smoothing…
A: Given: An initial trend forecast (T1) = 1.00 An initial exponentially smoothed forecast (F1) = 30.…
Q: What is an Advantage of the MAPE? a. It can be compared across different forecast items. b. It…
A: The mean absolute percentage blunder, otherwise called mean absolute percentage deviation, is a…
Q: Develop a 3-weck weighted average forecast for Week 4 through 9 with weights WI - W2 = W3 = 0.2 0.3…
A: A moving average based on weighted average puts weight on the data gathered recently, by multiplying…
Q: Calculate the forecast for Week 16 using - a 2-period moving average - a 3-period moving average…
A: Given data is
Q: Forecasts based on averages. Given the following data:PeriodNumber ofComplaints1 602 653 554 585…
A: Formula: Answer:
Q: Please show how you got part C
A: Year Demand Workings Forecasted Demand 4 10 0.20×7+0.25×9+0.55×5 6.4 5 13 0.20×9+0.25×5+0.55×10…
Q: Marianne Kramer, the owner of Handy Man Rent-als, rents carpet cleaners to contractors and…
A:
Q: Marianne Kramer, the owner of Handy Man Rent-als, rents carpet cleaners to contractors and…
A: MAD stands for Mean Absolute deviation which is defined as average distance among every data value…
Q: Clinic administrator Marc Schniederjans wants you to forecastpatient demand at the clinic for week 7…
A: Weighted moving average=∑Weight for period nDemand for period…
Q: Sales of tablet computers at Ted Glickman's electronics store in Washington, D.C., over the past…
A: A) Formulae used : Forecast = (1 - smoothing factor) * Most recent period forecast) + (Smoothing…
Q: The demand for Krispee Crunchies, a favorite breakfast cereal of people born in the 1940s, is…
A: Trend forecast is a quantitative data forecasting method where we use past data for finding out…
Q: The company's sales history (in thousands of units) is shown in the table below. Use exponential…
A: Concept and formulas used: FIT = Forcast Including Trend FIT = Ft + Tt Ft = FITt-1 + a…
Q: hillip Cane, the managing editor of Your Life Magazine, needs to develop a forecasting system for…
A: Month (2020) Sales May 50…
Q: National Standard, Inc. sells radio frequency identification (RFID) tags. Monthly demand for a…
A: Note: - Since we only answer up to 3 sub-parts, we’ll answer the first3. Please resubmit the…
Q: а. Write down the definition of Associative model forecast with appropriate example. b. Compute MAD,…
A: Forecasting involves victimization of past knowledge to come up with a variety, set of numbers, or…
Q: Marianne Schwartz, the owner of Handy Man Rentals, rents carpet cleaners to contractors and walk-in…
A:
Q: Sarah has been custom manufacturing sweaters now for 7 years. Her annual sales are shown below.…
A: Given data-
Q: Forecast is calculating estimates of future cycle/s based on data of past cycles, there is no…
A: Forecasting is the way toward making expectations dependent on over a significant time span…
Q: My problem asks me to Forecast using a "simple 4-month moving average" but when I calcualte that, I…
A: A) Month Units Sold May 1500 June 1400 July 1800 August 1500…
Q: Forecast is calculating estimates of future cycle/s based on data of past cycles -- there is no…
A: Forecasting is a prediction method that can use historical data and current market trends and…
Q: What effect does the number of cycles in a moving average have on the forecast's responsiveness?
A: In order to estimate potential demand, the Moving Average (MA) projection method uses the MA formula…
Q: a. Forecast April through September using a three-month moving average. b. Use simple exponential…
A: Below is the solution:-
Q: snip
A: A moving average forecast becomes less responsive to change in a data series when more data points…
Q: The manager of a popular tourist resort wants to use the manual trend projection forecasting…
A: The equation for exponential smoothing is- Ft = F t-1 + α(A t-1 – Ft-1) Ft = the exponentially…
Q: Consider the following time series data. Choose the correct time series plot. (i) (ii)…
A: A time series is a grouping of information focuses that happen in progressive requests throughout…
Q: Forecasts are generally wrong.a. Why are forecasts generally wrong?b. Explain the term “wrong” as it…
A: Forecasting generally means predicting or estimating something for future events. It is also about…
Q: A restaurant wants to forecast its weekly sales. Historical data (in dollars) for 15 weeks are…
A: Forecasting refers to the statistical technique used for predicting the future demand and sales of…
Q: Develop a three-week moving average. A.What is the forecast for week 5? (Make sure no decimal place…
A: Since you have posted a question with multiple sub-parts, we will solve the first three subparts for…
Q: a) Calculate the forecasted registrations for years 2 through 12 using exponential smoothing, with a…
A: ANSWER IS AS FOLLOWS:
Q: b) Use a 3-week weighted moving average, with weights of.1, .3, and .6, using.6 for the most recent…
A: Forecasting is the process of determining the estimated future demand using historical information…
Q: Jim's department at a local department store has tracked the sales of a product over the last five…
A: This question is related to the topic - Forecasting approach and this topic fall under The…
Q: Herman Hahn is attempting to set up an integrated forecasting and inventory controlsystem for his…
A: Time-series forecasting and seasonality factors in it:
Q: It has been said that forecasting using exponential smoothing is like driving a car by looking in…
A: Exponential smoothing is a time series forecasting technique for univariate data that can be…
Step by step
Solved in 4 steps with 4 images
- 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?The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six months of observations for validation purposes, use the method of moving averages with a carefully chosen span to forecast U.S. retail sales in the next year. Comment on the performance of your model. What makes this time series more challenging to forecast?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.
- The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?The file P13_26.xlsx contains the monthly number of airline tickets sold by the CareFree Travel Agency. a. Create a time series chart of the data. Based on what you see, which of the exponential smoothing models do you think will provide the best forecasting model? Why? b. Use simple exponential smoothing to forecast these data, using a smoothing constant of 0.1. c. Repeat part b, but search for the smoothing constant that makes RMSE as small as possible. Does it make much of an improvement over the model in part b?The file P13_29.xlsx contains monthly time series data for total U.S. retail sales of building materials (which includes retail sales of building materials, hardware and garden supply stores, and mobile home dealers). a. Is seasonality present in these data? If so, characterize the seasonality pattern. b. Use Winters method to forecast this series with smoothing constants = = 0.1 and = 0.3. Does the forecast series seem to track the seasonal pattern well? What are your forecasts for the next 12 months?
- 3. A mobile phone store owner wants to predict the demand for mobile phones in October based on the following historical sales data: Month- April May June. July August September Number of phones sold. 100, 140- 110. 150. 120. 160- a. What is this month's forecast using Naive approach b. Using 3-Month Moving Average, develop forecasts for October's demand c. Using 5-Month Moving Average, develop forecasts for October's demand d. When making moving average forecasts, is it better to use a larger time span? -2. An operation specialist used two forecast methods to forecast demand for a certain word processing software package. Actual demand and his corresponding predictions are shown below: Month Sales Forecast A Forecast B January 60 February 25 60 March 54 50 42 April 36 30 55 May 45 45 35 June 60 20 Which forecast method would you recommend if using MAD as the accuracy measurement? Select one: a. Forecast A b. Forecast B c. No preference.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
- 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.Please consider the following information and make forecasts for January, February, March, and April of Year 2. Use second-order polynomial regression to make forecasts. Adjusted seasonal index Actual sales Deseasonalized sales 836 825 Year 1 Year 2 January February March April May June July August September October November December January February March April 0.72 0.75 1:22 1.48 1 1.23 0.7 0.78 0.92 1.13 1.28 1.33 0.72 0.75 1.22 1.48 1220 1319 1020 1184 685 641 875 1008 1068 1141Explain the difference between qualitative and quantitative approaches to forecasting. Describe three (3) qualitative methods used in forecasting. Given the following data of demand for shopping carts at a leading supermarket. Prepare a forecast for period 6 using each of the following approaches: Period 1 2 3 4 5 Demand 60 65 55 58 64 A three-period moving average. A weighted average using weights of .50 (most recent), .20 and .30. Exponential smoothing with a smoothing constant of .40. The manager of a large cement production factory in Road Town, Tortola has to choose between two alternative forecasting techniques. His production staff used both techniques in order to prepare forecasts for a six-month period (See table below). Using MAD as a criterion, which technique has the better performance record? FORECAST MONTH DEMAND TECHNIQUE 1 TECHNIQUE 2 1 492 488 495 2 470 484 482 3 485…