Make a forecast of the demand for the month of January and February
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A: THE ANSWER IS AS BELOW:
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A: Given data is
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A: In forecasting techniques, the word "wrong" refers to a difference between the real and forecasted…
Q: snip
A: Answer: It is important to measure the accuracy of forecasts, for any forecasting technique and…
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A: A difference between real and forecasted values is referred to as "fake" in forecasting strategies.…
Q: Explain what benefits as a forecasting tool does exponential smoothing have over moving averages?
A: In today's environment, when events change frequently, the exponential smoothing method is superior.…
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A: 4-period weighted average forecast: Formula: Answer:
Q: The following table contains the demand from the last 10 months:…
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Q: When should time series forecasting techniques be used?
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Q: Daily high temperatures in st. Louis for the last week were as follows:…
A: Given information:Temperatures in last week is 33,33,38,36,43,23,28
Q: Given the following history, use a three-quarter moving average to forecast the demand for the third…
A: Given data is
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A: Forecasting is a method of predicting future trends, based on historical data.
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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…
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A: Weighted average forecast uses different weights which are assigned to past data to predict the data…
Q: The following table shows the actual demand observed over the last 11 years: Year 1 2 4 7 8 10 11…
A: Given - Table for demand seen in past years- Year Actual Demand 1 6 2 9 3 4 4 9 5 13…
Q: Explain the forecasting term with the help of least squares ?
A: Least Squares Method The least squares technique is a type of mathematical regression analysis that…
Q: What advantages as a forecasting tool does exponential smoothing have over moving averages?
A: A moving average forecast method takes into account instead of the last actual data, a number of…
Q: Explain what are the benefits of exponential smoothing over moving average forecasting
A: The table below gives a prediction of the advantages of moving average over exponential smoothing.
Q: Compute the weighted average forecast using the following weights: 0.20, 0.30, 0.10, and 0.40
A:
Q: Given the actual demand for years 2013/14, calculate the total forecast for year 2015, as well as…
A: Below is the solution:-
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Q: orecast demand for each week, including week 10, using exponential smoothing with a 5 .5 (initial…
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Q: What benefits does exponential smoothing have over moving averages as a forecasting tool?
A: As a forecasting function, exponential smoothing has the following benefits over running averages:…
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A: Forecasting is the process of prediction in which sales demand is estimated using historic…
Q: What is the term for forecasts used for making day-to-day decisions about meeting demand?
A: Forecasting is a technique used to predict future events using quantitative and qualitative methods…
Q: Explain what is an accurate forecast?
A: Making is the act of selecting a course of action from a reservoir of thoughts or ideas available to…
Q: Suppose the weekly demand for a call centre is shown in the table below. Apply the moving average…
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A: Formula:
Q: Explain FORECAST ACCURACY?
A: Forecasting is the process of estimating future demand using the present and past data. The demand…
Q: what is the advantage of using double exponential smoothing over regression?
A: You can use both double exponential smoothing and regression to forecast a demand pattern with a…
Q: What is seasonality?How do we forecast using data that has seasonality?
A: Seasonality in time series data is the occurrence of repetitive up and down cycles in series values…
Q: How do exponential smoothing have benefits over shifting.averages as a forecasting tool?
A: The benefits of exponential smoothing are as a prediction tool compared to moving averages.
Q: Given the actual demand of 300, the previous forecast of 300, and an alpha of 0.048 , which one of…
A: The actual demand =300 The previous forecast = 300 Alpha = 0.048
Q: Sales for a product for the past three months have been 203, 365, and 293. Use a three-month moving…
A:
Q: Forecast sales for the 11th period. For leveling, use exponential smoothing 0.20 and moving average…
A: Use exponential formula = α×Actual demand+(1-α)×previous demand
Q: The following monthly sales (in thousands of AUS dollars) of chocolate boxes have been recorded for…
A: Forecasting is a method of foretelling the future based on the outcomes of earlier data. It includes…
Q: Sales for Pandora’s Jewellery for the past three months have been 200,350, and 287. Use a…
A: Given data; Three months actual demands are 200,350,287. Fourth month actual demand = 300
Q: Provide an example of a Quantitative forecast in air cargo or other industry
A: Cargo forecasts are generally tackled as part of an airport's master planning activity, as part of…
Q: orecast sales for the 11th period. For leveling, use exponential smoothing 0.20 and moving average 3…
A: THE ANSWER IS AS BELOW:
Q: Discuss what is seasonality and how forecast is done using data that has seasonality?
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Q: Discuss what advantages as a forecasting tool does exponential smoothing have over moving averages?
A: In today's environment, when events change often, the exponential smoothing method is optimal.…
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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.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_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 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_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?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_19.xlsx contains the weekly sales of a particular brand of paper towels at a supermarket for a one-year period. a. Using a span of 3, forecast the sales of this product for the next 10 weeks with the moving averages method. How well does this method with span 3 forecast the known observations in this series? b. Repeat part a with a span of 10. c. Which of these two spans appears to be more appropriate? Justify your choice.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_27.xlsx contains yearly data on the proportion of Americans under the age of 18 living below the poverty level. 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. Create a chart of the series with the forecasts superimposed from this optimal smoothing constant. Does it make much of an improvement over the model in part b? d. Write a short report to summarize your results. Considering the chart in part c, would you say the forecasts are good?
- 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?Under what conditions might a firm use multiple forecasting methods?The 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 150a. Using the following, forecast the sales for the months up January the following yeariii. Exponential Smoothing when α= .6 and the forecast for March is 350.
