A time-series forecasting model uses a series of past data points to make a forecast. True False
Q: Both time series and causal forecasting assume that the past relationship between demand and the…
A: Time series forecasting refers to the prediction of future events of a business. According to the…
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: Series forecasting for Business| The F-test used in testing the significance of a regression model…
A: The correct answer is
Q: Based on the given data below: compute for the Forecast on Day 8 using the Weighted Moving Average…
A: The answer is as below:
Q: Using the data set below, what would be the forecast for period 5 using the exponential smoothing…
A: Forecasting is the process of estimating future sales or demand using previous data and information.…
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: 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: Simple exponential smoothing with a 5 0.3 is being used to forecast sales of digital cameras at…
A: Given Smoothing constant a=0.3 Forecast for September = 100 cameras Sales in September = 120 cameras
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: Describe and evaluate the method of forecasting based on a time series analysis when a trend is…
A: Forecasting is the practice of estimating the size of unknown future events and generating different…
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: Forecasts may be influenced by a product's position in its life cycle.. A) TRUE B) FALSE
A: The life cycle of a product defines the different stages from its beginning to its end in the market…
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: The plot of the time series helps to decide about the best model to be used for forecasting O a True…
A: Th answer for the above question is as follows:
Q: A company has an unbiased forecast for its demand. What does that mean?a. All forecast errors are…
A: Forecasting is the procedure of prediction making for the future grounded on past as well as present…
Q: When calculating the moving average forecast using Excel, ____ is entered into the “Interval” box in…
A: The moving averages method uses the average of the most recent data values in the time series as the…
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: Is there anything that can be done to boost the Forecast technique
A: Forecasting is a technique for forecasting potential demand, assessing risk, and analysing patterns.…
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: snip
A: Forecasting is a technique of estimating or predicting future trends with the help of surveyed data…
Q: is based on the principle of using only the last observation in a sequence of stable data as a…
A: Here, question has asked about the specific forecasting technique that would be based on the…
Q: You have a data set that includes time period and past sales data, and you want to use a time series…
A: Ans// D) Weighted moving average Time series forecasting makes the prediction about the future by…
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: Forecasts are generally wrong.a. Why are forecasts generally wrong?
A: Forecasting is used to predict future changes or demand patterns. Forecasting is the process of…
Q: All the following are techniques used in quantitative forecasting except. A. Regression analysis B.…
A: Forecasting refers to the approach of making predictions on the basis of present and past…
Q: Which of the following is a forecasting error measure? A. CAT B. SAD C. MAD D. BAD
A: (C) MAD MAD is used to measure the forecast Error
Q: Forecast bias is useful to determine a. Seasonality b. Trends c. if forecast error is…
A: A forecast bias happens when there are differences between actual outcomes and previously generated…
Q: Through forecasting, organizations attempt to adapt to or change the future as predicted through…
A: This do not require any introduction
Q: Which time-series forecasting method works best if the company assumes that product demand will…
A: Forecasts are a basic input in the decision processes of operations management because they provide…
Q: How can we monitor and control forecast in our interior designing business. Please provide with a…
A: Small Introduction about Forecast Control Because forecast explosion only creates exploded forecast…
Q: Forecasting is a prediction rather than a reality
A: The term forecasting is a technique that uses the historical data as inputs to make the informed…
Q: Exponential Smoothing gives always better results than any other similar method used for time-series…
A: Forecasting in the business management is described as the process through the probable demand in…
Q: snip
A: A moving average forecast becomes less responsive to change in a data series when more data points…
Q: Explain the effects it does on the no. Of cycles in a moving average have on the forecasts…
A: A Moving Average (MA) forecasting method estimates anticipated demand by calculating the average…
Q: Forecasts are generally wrong.a. Why are forecasts generally wrong?b. Explain the term “wrong” as it…
A: Forecasting generally means predicting or estimating something for future events. It is also about…
Q: 2. Simple moving average using Excel: Calculate demand forecast for weeks 6-20 using 5 week simple…
A: Forecasting is predicting the demand/sales in advance for future periods. Moving average forecast is…
Q: is a method that utilizes the principle of using only the last observation in a sequence of stable…
A: ________ is a method that utilizes the principle of using only the last observation in a sequence of…
Q: Qualitative or judgmental forecasting models may use quantitative data. True False
A: False
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: A restaurant wants to forecast its weekly sales. Historical data (in dollars) for 15 weeks are…
A: Forecasting refers to the statistical technique used for predicting the future demand and sales of…
Q: Using the latest observation in a sequence of data to forecast the next period is a. a naive…
A: Find the answer below: The Correct answer is a) a naïve forecast
Q: Consider the following actual and forecast demand levels for Big Mac hamburgers at a local…
A: Let, Ft+1 = Forecast for friday Yt = 48.00 Ft = 77.60 α = 0.40 Thus expression for the forecast for…
Q: The errors in a particular forecast are as follows: 3, -3, 4, 0, -2. What is the tracking signal for…
A: Error = Actual demand - forecast Absolute Error = Positive value of error MAD = average of…
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: Explain the term Forcasting
A: In getting ready designs for the future, the administration authority needs to make a few…
Q: The Victory Plus Mutual Fund of growth stocks has had the following average monthly price for the…
A: Note: - Since we can answer only up to three subparts we will answer the first three(1, 2, and 3)…
-
A time-series
forecasting model uses a series of past data points to make a forecast.- True
- False
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
- 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 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 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_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?Construct a time series plot. What type of pattern exists? Develop a forecast for the next month using the averaging method. Develop a forecast for the next month using the naïve last-value method.
