Year QuarterSales 20181 2018 2 2018 3 2018 4 20191 2019 2 20193 20194 20201 20202 45 44 48 47 Suppose that Brown's exponential smoothing with a smoothing constant of 0.10 was used to forecast sales and the predicted sales value for the first quarter of 2020 is found to be 46.7. Forecast sales for the fourth quarter of 2021.
Q: Weekly sales of copy paper at Cubicle Suppliers are in the table below. Compute a three- period…
A: This question is related to the topic -Forecasting and this topic would fall under the business…
Q: Simple exponential smoothing with α= 0.3 is being used to forecast sales of digital cameras at…
A: Given Information: Sales in September: 120 units Forecast in September: 100 units Alpha = 0.3…
Q: Demand for oil changes at Garcia’s Garage has been as follows:Month Number of Oil…
A: The following dialogue box will appear. Enter the data and click on OK.
Q: The following data relate the sales figures of the bar in Mark Kaltenbach's small bed-and-breakfast…
A: Given data is
Q: For the E-Commerce Retail Sales (Million$) data given in the table below, provide estimates from the…
A: Given data is
Q: Problem 1: The following data was taken from experiment. The data can be modeled by the following…
A: given,
Q: Two forecasting methods were used to forecast the next 12 quarters. The forecasts and actuals for…
A:
Q: In the Atlanta area, the number of daily calls for the repair of Speedy copy machines has been…
A: Given data-
Q: 2. The production and corresponding costing of a product in a factory is given below: Production…
A:
Q: Consider the following time series data. Week 1 2 3 4 5 6 Value 18 13 16 11 17 14 a. Construct a…
A: Given information Week Value 1 18 2 13 3 16 4 11 5 17 6 14
Q: Quesiton-4 :Weekly demand for dry pasta at a supermarket chain is as follows: Week Demands 1 517…
A: Given data, Week Demands 1 517 2 510 3 557 4 498 5 498 6…
Q: The intuition behind the MSE metric to evaluate old forecasts is:a. to sum up the forecast errors.b.…
A: Forecast helps in identifying the trend of data by analyzing the past data. Forecast does not…
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: The table below shows the quarterly sales of television set (in thousands) in an electrical…
A: Seasonal variation will be variation in a period series inside one year that is rehashed pretty much…
Q: The total sales of a company doing business from Monday through Saturday. Number of Motor…
A: The practice of analyzing data collected at various points in time is known as time series analysis.…
Q: The demand (in number of units) for Apple iPad over the past 6 months at BestBuy is summarized…
A: 2-month weighted moving average: Formula: Answer:
Q: Specifically, it wants to provide a 99% confidence level and a cycle time that is within 2% of the…
A: We will find the mean, standard deviation and other relevant values and then calculate the number of…
Q: 9. a. Obtain the linear trend equation for the following data on new checking accounts at Fair Sav…
A: A trend line is a finest fit straight-line cast-off through liner data sets which support to…
Q: Use Holt’s double exponential smoothing with smoothing coefficients α=0.3, β=.15, S1=24.13 and…
A: THE ANSWER IS AS BELOW:
Q: 1. Solve manually. a. Income at the law firm Smith and Wesson for the period February to July was as…
A: Regression is a statistical technique used in finance, investing, and other fields to identify the…
Q: The following tabulations are actual sales of units for six months and a starting forecast in…
A:
Q: The Samuel Bridge Company wants to compare the accuracy of three methods that it has used to…
A: Formulas: Error= Actual -Forecast Squared Error = Error2 Mean Square Error (MSE) = ∑Squared ErrorNo.…
Q: For the Petroco Service Station problem, what would your excel file that shows exponentially…
A: Forecasting refers to predictions for future outcomes based on previous years' trends. In businesses…
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: Freight car loadings over an 18-week period at a busy port are as follows: Weeks Loadings (lbs)…
A: Let X denotes the week and Y denotes the number. Now calculate the following:
Q: A coffee shop owner wants to estimate demand for the next four quarters for hot chocolate. Sales…
A: Given, Quarter 1- 1.20 Quarter 2- 1.15 Quarter 3- 0.77 Quarter 4- 0.88
Q: A company wants to forecast demand using the weighted moving average. If the company uses two prior…
A: Weighted moving average (WMA) = Wt * Vt
Q: Sales of industrial vacuum cleaners at Larry Armstrong Supply Co. over the past I 3 months are shown…
A: Note: As per the Bartleby guidelines only the first three parts have been answered.
Q: Dr. Lillian Fok, a New Orleans psychologist, spe-cializes in treating patients who are agoraphobic…
A: Yc = a +bxb = n(∑xy) - (∑x)(∑y)n(∑x2) - (∑x2)a = ∑y - b∑xn or, y -bxYc = computed value of…
Q: A company that supplies gasoline to a city has recorded the weekly usage (tons/week) for the past 3…
A: Find the Given details below: Given Details: Week Demand (tons) 1 1174.5 2 1316.2 3 1197…
Q: 8.) Create an exponential smoothing model that minimizes the MSE for the data set. Use Solver to…
A:
Q: The manager of a utility company in the Texas panhandle wants to develop quarterly forecasts of…
A: Seasonal index = season demand / average yearly demand Seasonal index when multiple periods are…
Q: A company has observed the following demand during the past 10 months for one of its popular…
A: *As per guidelines for multipart questions first three parts are answerable, please repost the…
Q: 4.31 Emergency calls to the 911 system of Durham, North Carolina, for the past 24 weeks are shown in…
A: Given data is
Q: Hassan owns a company that manufactures sailboats. Actual demand for Hassan's sailboats during each…
A:
Q: The number of heart surgeries performed at Heartville General Hospital has increased steadily over…
A: Since you have submitted a question with multiple sub-parts as per guidelines we have answered the…
Q: A small hospital is planning for future needs for Çovid 19. The data below show the number of cases…
A:
Q: Attendance at Orlando's newest Disneylike attraction, Lego World, has been as follows Quarter Winter…
A: To determine the Seasonal indices of the year by using formulae: Total attendance for the year =…
Q: Consider the following time series data. Week 1 2 3 4 5 6 Value 19 14 16 12 17 15 A. Develop the…
A:
Q: The number of auto accidents in Athens, Ohio is related to the regional number of regisgtered…
A: Given values: Regression formula; y=a+b1X1+b2x2+b3X3 where, Y = number of automobile accidents a =…
Q: The classified department of a monthly magazine has used a combination of quantitative and…
A:
Q: 2 Vidhya Balan is planning to liquidate her investments in mutual funds and invest in real estate.…
A: Find the Given details below: Given details: Month Average Fund Price 1 55.1 2 53.8 3…
Q: The manager of a utility company in the Texas panhandle wants to develop quarterly forecasts of…
A:
Q: Suppose that you are given the following sales data for the last three years, with Q1 being Quarter…
A: Solution a) 1. Calculate average demand per season by dividing annual demand by number of quarters…
Q: An additive Holt-Winters forecast is being performed on accounting industry revenue data. Revenue…
A: Find the given details below: Given details: Date Time Revenue($ billions) lt bt st Forecast…
Q: a Compute MAD for the results of each forecasting method. Which one is more accurate? b Compute MSE…
A: Forecasting is a technique used to predict future outcomes on the basis of past data. In businesses…
Q: 2 Vidhya Balan is planning to liquidate her investments in mutual funds and invest in real estate.…
A: Find the Given Details below: Given Details: Month Average Fund Price 1 55.1 2 53.8 3…
Q: The last-value forecasting method: a. is quick and easy to prepare. b. is easy for users to…
A: A strategy that uses previous data as inputs to make well-informed predictions about the direction…
3
Step by step
Solved in 2 steps with 2 images
- 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 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?Under what conditions might a firm use multiple forecasting methods?
- 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_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 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_02.xlsx contains five years of monthly data on sales (number of units sold) for a particular company. The company suspects that except for random noise, its sales are growing by a constant percentage each month and will continue to do so for at least the near future. a. Explain briefly whether the plot of the series visually supports the companys suspicion. b. By what percentage are sales increasing each month? c. What is the MAPE for the forecast model in part b? In words, what does it measure? Considering its magnitude, does the model seem to be doing a good job? d. In words, how does the model make forecasts for future months? Specifically, given the forecast value for the last month in the data set, what simple arithmetic could you use to obtain forecasts for the next few months?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?The file P13_28.xlsx contains monthly retail sales of U.S. liquor stores. 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?
- Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.The file P13_25.xlsx contains the quarterly numbers of applications for home mortgage loans at a branch office of Northern Central Bank. 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? Is it guaranteed to produce better forecasts for the future?A small computer chip manufacturer wants to forecast monthly ozperating costs as a function of the number of units produced during a month. The company has collected the 16 months of data in the file P13_34.xlsx. a. Determine an equation that can be used to predict monthly production costs from units produced. Are there any outliers? b. How could the regression line obtained in part a be used to determine whether the company was efficient or inefficient during any particular month?