Q: orecasting is the primary function for predicting the future using the available data to make the…
A: Forecasting is the primary function for forecasting the future and making decisions based on the…
Q: Geries forecasting for Business In a regression model if you drop one insignificant variable then O…
A: The correct answer is
Q: The solution of coping with natural differences between marketing and production functions is to do…
A: Option 1: - When natural differences occur in production and marketing it is necessary to have…
Q: a. Construct a time series plot. What type of pattern exists in the data? b. Compare a two-week…
A: Forecasting is predicting in advance the values through various methods like moving averages,…
Q: In exponential smoothing, if ɑ = 0.3, then the damping factor for use in forecasting should be: *…
A: Exponential smoothing is a forecasting method which identify the forecasting value using the…
Q: Forecasting, whether quantitative or qualitative in nature, is used every day in all business to…
A: Forecasting is an approach to expecting the tomorrow based on the outcomes of earlier data. It…
Q: Which of the following smoothing constant would make an exponential smoothing forecast equivalent to…
A: alpha of 1.0 leads to an exponential smoothing forecast similar to a naive forecast.
Q: Explain what is seasonality and how forecast is done using data that has seasonality
A: In time series analysis, seasonalities are regarded as repeated up / down cyclic patterns in serial…
Q: Which of the following smoothing constants would make an exponential smoothing forecast equivalent…
A: In exponential smoothing, it is attractive to utilize a higher smoothing consistent when…
Q: After using your forecasting model for six months, you decide to test it using MAD and a tracking…
A: Here we use formulae: Formulas: Tracking Signal (TS) is presented by:TS = RSFEMAD RSFE = Running…
Q: What type of analytics seeks to recognize what is going on as well as the likely forecast and make…
A: Analytics which involves predictions based on historical and current data is known as predictive…
Q: 9-The approach that uses the organization's current level of employment as the starting point for…
A: Every business enterprise is required to assess its staffing requirements over a specific time…
Q: Forecasting is the basis for all strategic and planning decisions in the supply chain. Select one:…
A: Find the answers below: The Correct answer is True.
Q: State and explain three methods that are used to determine the accuracy of any given forecasting…
A: To be determined: three methods that are used to determine the accuracy of any given forecasting…
Q: snip
A: An exponential smoothing forecast becomes more responsive to changes in a data series when its alpha…
Q: What does the word "biassed" mean when applied to a specific forecasting technique?
A: Forecasting is a common and widely used methodology in almost every area of endeavor, including…
Q: Forecasts are usually classified by time horizon into three categories a. finance/accounting,…
A: Forecasts are usually classified by time horizon into three categories finance/accounting,…
Q: If the Tracking Signal for your forecast was consistently positive, what could you then say this…
A: If the tracking signal of the forecast is always positive, then it is bias and consistently too low.…
Q: Consider the time series data in Table 4 Construct a time series plot. What type of pattern exists…
A: Moving average and exponential smoothing methods are time series forecasting method. This can be…
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: pros and cons of doing that? Give three examples of unethical conduct involving forecasting and the…
A: Unethical behavior takes place in forecasting when an analyst specifies a particular data to create…
Q: Registration numbers for an accounting seminar over the past I 0 weeks are shown below:…
A: Note: “Since you have posted a question with multiple sub-parts, we will solve the first three…
Q: Explain what ex-post and ex-ante forecasts are, and how one can evaluate the accuracy of forecast of…
A: Ex Post Forecast, Ex Ante Forecast Ex post is forecasting using data that has been collected after…
Q: Explain the trade-off between responsiveness and stability in a forecasting system that uses…
A: Forecasting is the process of making assumptions of the future on the basis of past and present data…
Q: is based on the principle of using only the last observation in a sequence of stable data as a…
A: Option C is correct. The naive forecast is based on the principle of using only the last observation…
Q: 2-The correlation between rate and base are called the dynamic forecast. Select one: O True O False
A: Correlation is described as the relationship that exists between two different variables…
Q: A) What makes a forecast optimal?
A: A) Practically all administrative choices depend on Forecasting. Each choice becomes functional…
Q: Forecasting plays an important role in the operations of modern management. In fact, operational…
A: Forecasting can be defined as the process of estimating data based on the present and past data.…
Q: forecasting methods across different data sets?
A: Calculating the accuracy of a Forecasting method is focusing to choose the best forecasting method…
Q: a. They generally work best when combined with a quantitative approach
A: Qualitative research comes from open-ended questions. It collects data in a different way. Instead…
Q: determines the length of the future time period for which a sales forecast must be prepared for…
A: Planning is a fundamental activity of management. Forecasting forms the basis of planning. Be it…
Q: Three popular measures of forecast accuracy are: average error, median error, and maximum error.…
A: The accuracy of the forecast can be determined by comparing the actual or real values with the…
Q: Suppose you need to forecast the amount of relief aid needed following an earthquake. What type of…
A: Answer: Relief aid needed following an earthquake, belong to the category of disaster relied supply…
Q: Forecasting plays an important role in the operations of modern management. In fact, operational…
A: Answer: Reference: Wikipedia, Operations Management book, Pearson Publication, 12e Kimberly-Clark…
Q: Through forecasting, organizations attempt to adapt to or change the future as predicted through…
A: This do not require any introduction
Q: discuss
A: The answer to this question is false.
Q: Plot these forecasts AND the original demand data on graph paper or spreadsheet. Use a key to…
A: Find the given details below: Given details: Period Original Demand 3 Months Moving average 5…
Q: A check-processing center uses exponetial smoothing to forecast the number of incoming checks each…
A: Given, Checks received in June = 40 million Forecast for June = 42 million Smoothing Constant = 0.15
Q: Time-series analysis is based on the assumption that: a. there are dependable correlations between…
A: According to above questions Time series analysis and forecasting are based on the assumption that…
Q: None of the options are correct.
A: What is Stationarity? A time collection has stationarity if a shift in time doesn’t purpose an…
Q: How does the linear trend line forecasting model differ from a lincar regression model for…
A: Linear trend line forecasting refers to the statistical tool that helps in better interpretation of…
Q: a. Find the tracking signal for each month. (Negative values should be indicated by a minus sign.…
A: Based on the above provided question, the tracking signal for each month can be obtained as below:
Q: The moving average forecast method should only be used with time series data demonstrating a linear…
A: A moving average, which is indeed the average of any subset of values, is a method for gaining a…
Q: Two forecasting models were used to predict the future value of a time series. These are shown in…
A: Mean Absolute Deviation(MAD) and Mean Squared Error (MSE) are the two most commonly used…
Q: The following table shows predicted product demand using your particular forecasting method along…
A: From the above given information, we have to compute the tracking signal of each period using the…
Q: All forecasts are built on one of three information bases: what people say, what people do, or what…
A: The рrосess оf gаthering infоrmаtiоn fоr а better understаnding оf the tаrget mаrket is…
Q: What is time series decomposition? Why would a forecaster choose this method versus some of the…
A: Time series information can show an assortment of examples, and it is regularly useful to part a…
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…
Q: Demand forecasting is the primary data for decision-making in any organization. What will happen if…
A: The term demand forecasting refers to a process under which an organization intends to use the…
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- Under what conditions might a firm use multiple forecasting methods?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_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_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 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_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?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_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?
- 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?Suppose that a regional express delivery service company wants to estimate the cost of shipping a package (Y) as a function of cargo type, where cargo type includes the following possibilities: fragile, semifragile, and durable. Costs for 15 randomly chosen packages of approximately the same weight and same distance shipped, but of different cargo types, are provided in the file P13_16.xlsx. a. Estimate a regression equation using the given sample data, and interpret the estimated regression coefficients. b. According to the estimated regression equation, which cargo type is the most costly to ship? Which cargo type is the least costly to ship? c. How well does the estimated equation fit the given sample data? How might the fit be improved? d. Given the estimated regression equation, predict the cost of shipping a package with semifragile cargo.Stock market analysts are continually looking for reliable predictors of stock prices. Consider the problem of modeling the price per share of electric utility stocks (Y). Two variables thought to influence this stock price are return on average equity (X1) and annual dividend rate (X2). The stock price, returns on equity, and dividend rates on a randomly selected day for 16 electric utility stocks are provided in the file P13_15.xlsx. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Also, interpret the standard error of estimate and the R-square value for these data.