Why the following Approaches are used in forecasting, how would you interpret them what do they mean explain in detail and write down the analysis that shows the purpose of these approaches. 1. Naive approach 2. Moving averages 3. Exponential smoothing 4. Trend projection 5. Linear regression
Q: Discuss when to use a time series forecasting techniques ?
A: Historical data, and hence projected variables, are subjected to statistical analysis. The…
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: When forecasting demand for new products, sometimes i rms will use demand data from similar existing…
A: Demand forecasting is the technique used by managers to forecast the expected future demand and…
Q: Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend,…
A: The types of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend,…
Q: What is the forecast using exponential smoothing with alpha = .6? 2. If we decide to…
A: ANSWER IS AS FOLLOWS:
Q: Discuss the basic assumptions made when using time series forecasting techniques as opposed to…
A: Several assumptions are made during the Time Series Initial Phase.
Q: What are the similarities and differences between ridge regression and forecasting?
A: A Small Introduction about Regression Regression analysis is used to predict a continuous dependent…
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.…
Q: In your own words and it should be in paragraph form. Also, don't forget to conclude. 1. Identify…
A: Forecasting is the process of making assumptions of the future on the basis of past and present data…
Q: All forecasting methods using exponential smoothing, adaptive smoothing, and exponential smoothing…
A: Forecasting is the process of predicting future demand values based on historical data. The…
Q: Table 3 Percent change in income Percent Change in appliance sold Quarter Percent change in income…
A: (a) Here, the relationship between two variables needs to be identified, so a linear regression…
Q: It has been said that forecasting using exponential smoothing is like driving a car by looking in…
A: As there are multiple questions posted, as per policy will answer the first question only. If you…
Q: Which of the following is used to describe the degree of forecast error? a. Median and Mode b. Mean…
A: Mean absolute percent error is the method to describe the degree of relationship between errors for…
Q: In order to increase the responsiveness (volatility) of following forecast models, what can you do?…
A: In order to increase the responsiveness of the forecast model using exponential smoothing, we need…
Q: Do you think that hard rock cafe makes use of time horizons when forecasting?
A: The forecast horizon is that the duration of your time into the destiny that forecasts are to be…
Q: What th ree methods are used to determine the accuracy of any given forecasting method? How would…
A:
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: Which qualitative forecasting technique was developed to ensure that the input from every…
A: Delphi method.
Q: Consider the data below which includes sales data and the forecasts that would have been made using…
A: Given data is
Q: Forecasting time horizons include:a) long range. b) medium range.c) short range. d) all of the…
A: Forecasting is that of the method by that managers make estimates about future events. It's…
Q: At the ABC Floral Shop, an argument developed between two of the owners, Bob and Henry, over the…
A: A simple exponential smoothing method is used for smoothing time series data by assigning…
Q: Explain what forecasting techniques makes use of written surveys or telephone interviews
A: Operations management manages the internal operation. It starts with the procurement and ends with…
Q: What method would you choose of forecasting technique, which requires subjective inputs obtained…
A: Forecasting is technique which uses past data in order to predict future trends. It is mainly used…
Q: Accuracy of forecasts. The manager of a large manufacturer of industrial pumps must choose…
A: Given data, Assume that each forecast has an average error of zero. Forecast Month…
Q: What should be our forecast accuracy target if there is a high degree of volatility in customer…
A: Thank you for you question. As per our guidelines, We will be answering the first question for you…
Q: Using MAD as a criterion, which technique has the better performance record?
A: MAD or Mean Absolute Deviation indicating the average value of the absolute errors. An efficient…
Q: Which qualitative forecasting technique was developed to ensure that the input fromevery participant…
A: Forecasting is the way toward making forecasts of things to depend on at various times information…
Q: I got super lost on this one, the correct answers are shown but not how they solved or got to the…
A: Formula: Answer:
Q: Here are the errors associated with a particular forecast over the past five months, in…
A: Forecasting is a methodology that uses past information as input to make well-informed predictions…
Q: Suppose you are working for a baking company in Bangladesh. What are the relevant factors you will…
A: Forecasting is the activity of making estimations of future activities based on past and present…
Q: The manager of a large manufacturer of industrial pumps must choose between two alternative…
A: Both techniques have been used to prepare forecasts for a six month period as follows:
Q: Justify the trade-off between responsiveness and consistency in a time-series forecasting system.
A: TradeoffTradeoff is a situational decision taken approach, that involves diminishing quality,…
Q: Choose the type of forecasting technique (survey, Delphi, averaging, seasonal, naive, trend,…
A: Seasonal forecast is a type where the prediction is done only in that particular season. This is…
Q: Briefly mention the five characteristics of data patterns in time series method of forecasting.
A: Time series forecasting happens when making a scientific projection based on documented or…
Q: Forecasting time horizons include:a) long range. b) medium range.c) short range. d) all of the…
A: Forecasting refers to making decisions and predicting on the basis of previous or past experiences.
Q: Explain the difference between qualitative and quantitative approaches to forecasting. Describe…
A: Forecasting is the method of forming foresight dependent on historical and existing or present…
Q: Explain how do exponential smoothing have benefits over shifting averages as forecasting tool
A: The merits of autoregressive moving as a prediction approach are considerable in comparison to…
Q: onsider the following time series data. Week 1 2 3 4 5 6 Value 18 12 15 11 18 13 Using the…
A: Given that: Week Value 1 18 2 12 3 15 4 11 5 18 6 13
Q: ontrast the reactive and proactive approaches to forecasting. Give several examples of types of…
A: Forecasting: Forecasting is a technique and a method which takes into consideration a set of…
Q: . What is the mean square error for time periods 2 through 4 using the average forecasting method?…
A: I am using the 2 periods simple moving average method to find average forecasts. It is the average…
Q: Discuss the basic assumptions made when using time series forecasting techniques as apposed to…
A: Time series forecasting fundamental assumptions:
Q: How many steps are there in collaborative planning, forecasting, and replenishment (CPFR)?
A: There are 9 steps in collaborative planning, forecasting, and replenishment (CPFR). They are:
Q: The manager of a travel agency asked you to come up with a forecasting technique that will best fit…
A: Given - Smoothing constant (α) = 0.25 Period Demand F1 F2 1 115 - - 2 176 - - 3 97 146…
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.…
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…
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- 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 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_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_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_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_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?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?
- 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?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.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.