Consider then, the nature and characteristics of forecasting. What do you think the difficulties or obstacles to accurate forecasting might be? Submit and explain as many of these difficulties as you can think of.
Q: Explain the term “wrong” as it pertains to a good forecast?
A: In forecasting techniques, the word "wrong" refers to a difference between the real and forecasted…
Q: The sales and profit of a clothing organization are represented in the table below. This given data…
A: 1. Following are three advantages of forecasting within an organization: A)You'll acquire…
Q: Describe the characteristics and differences between qualitative, quantitative, extrinsic,…
A: Forecasting techniques are used to predict the present and future events which helps in analysing…
Q: Explain the trade off of responsiveness in a time series forecasting system
A: In return for improvements on other issues, Tradeoff is a situation-based technique that entails…
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: 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: Explain what are the forecasting process principles?
A: Forecasting is the science of forecasting what will occur in the future based on past and current…
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: What are ways of managing a poor forecast?
A: A bad forecast presupposes that there has been a mismatch between the demand and supply as a result…
Q: Explain what are the use of a time series forecasting and discuss what assumption are made ?
A: Globalization is the process of bringing together individuals, businesses, and governments on a…
Q: What is the value of your forecast? PX If instead the weights were 20, 15, 15, and 10, respectively,…
A: ANSWERS ARE GIVEN BELOW:
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: Identify the major differences between qualitative and quantitative forecasting.
A: Forecasting can be defined as the technique which predicts the future information based on…
Q: 20- Forecasting is very important in predicting the future sales of a company. Can you identify the…
A: Below is the solution;-
Q: We have a new chief sales officer who is proposing that we should forecast in dollars, not in…
A: Salespeople are inexperienced with estimate exactness measures. They have no real excuse to be on…
Q: What is the strategic importance of forecasting for a business such as Pinkie Ice Cream ? What are…
A: Strategic Management Strategic management gives general way by creating plans and approaches…
Q: Consider the data below which includes sales data and the forecasts that would have been made using…
A: Given data is
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 is forecast accuracy and what are the different methods to check it?
A: Forecast Accuracy is basically how accurately the predicted value matches the actual value. In…
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: A) What makes a forecast optimal?
A: A) Practically all administrative choices depend on Forecasting. Each choice becomes functional…
Q: Explain the term forecasting with least squares
A: Forecasting is a way of making a broader basis about the coming supported by facts. It can be used…
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: All forecasts are subject to error. Do you think topmanagers would be concerned about the effectson…
A: Forecasting is described as a tool that will allow the businesses in the budgeting process and also…
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: What are the main advantages that quantitative techniques for forecasting have over qualitative…
A: Forecasting is the process of estimating potential demands as well as the resources that will be…
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: Discuss the strategic importance of forecasting. What strategic decisions do organizations need to…
A: There is a huge competition between all the organizations these days to excel themselves in their…
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: Forecasting is critical in modern times. Business organizations manifested more concern with…
A: It is at the national, industry, and firm levels that business forecasting takes place. Forecasts…
Q: Write from your understanding the meaning of forecasting, forecasting time horizons, Seven Steps in…
A: Forecasting is a procedure that utilizations verifiable information as contributions to make…
Q: Discuss the basic assumptions made when using time series forecasting techniques as apposed to…
A: Time series forecasting fundamental assumptions:
Q: Why the following Approaches are used in forecasting, how would you interpret them what do they mean…
A: Forecasting is a technique that a marketer uses to estimate various things like a trend, future…
Q: Give a proper explanation of what is meant by the adaptive forecasting
A: To be determined: a proper explanation of what is meant by the adaptive forecasting
Q: List down some of the factors that may affect forecasting? What is the bases of forecasting
A: Forecasting is a process that uses historical data as information to make informed estimations that…
Q: What is the strategic importance of forecasting for a business such as One Stop Car Repairs? What…
A: Forecasting is a technique that uses historical data as inputs to make estimates that are predictive…
Q: Explain how the technology of forecasting can be improved
A: Forecasting is a long-term and short-term activity that the company engages in on a regular basis.…
Q: Calculate and answer parts a through d. Include all calculations and spreadsheets in your post.…
A: Formula: Answer:
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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_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?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_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?
- 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.
