14. Consider the following time series. t 1 2 3 4 5 7 Yt 120 110 100 96 94 92 88 a. Construct a time series plot. What type of pattern exists in the data? b. Develop the linear trend equation for this time series. C. What is the forecast for t = 8?

14. Consider the following time series. t 1 2 3 4 5 7 Yt 120 110 100 96 94 92 88 a. Construct a time series plot. What type of pattern exists in the data? b. Develop the linear trend equation for this time series. C. What is the forecast for t = 8?

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter13: Regression And Forecasting Models

Section13.6: Moving Averages Models

Problem 22P: The file P13_22.xlsx contains total monthly U.S. retail sales data. While holding out the final six...

See similar textbooks

Related questions

Q: Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17…

A: The concept used here is forecasting with Moving averages and forecast evaluation using MAE, MSE and…

Q: Week Actual Forecast Demand 1 52 48 2 42 46 3 56 52 4 45 47 true or false Assume that the actual…

A: The table shows the calculation of forecast of demand using the simple moving average method with 3…

Q: Following are two weekly forecasts made by two different methods for the number of gallons of…

A: A robust measure of how to spread out a set of data is the median absolute deviation (MAD). The…

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: Month 1 2 3 7 8 9 10 11 12 Flat-Screen Sales 30 32 30 39 33 34 34 38 36 39 30 36 a) Determine the…

A: Find the given details below: Given Details: Month Flat Screen Sales 1 30 2 32 3 30 4…

Q: The table below shows the demand for a particular brand of microwave oven in a department store.…

A: Given-

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: An analyst must decide between two different forecasting techniques for weekly sales of roller…

A: Given data-

Q: a) Plot the monthly sales data. b) Forecast January sales using each of the following: i) Naive…

A: Forecasting is a technique that uses historical data as information to make informed assessments…

Q: Determine the Running Sum of Forecast Errors (RSFE), the Mean Absolute Deviation, MADt-1,and the…

A: Forecasting is the process of predicting future demand based on previous or historic information and…

Q: Exponential smoothing is used to forecast automobile battery sales. Two value of a are examined, a =…

A: Given information:

Q: A skeptical manager asks what long-range forecasts can be used for when the CEO ask her to prepare…

A: Forecasting can be defined as the technique which uses past data to estimate future events.…

Q: 1. Consider the total production (and sales) of ice cream in Canada (in millions of liters) for the…

A: We are authorized to answer three subparts at a time since you have not mentioned which part you are…

Q: 9. a. Obtain the linear trend equation for the following data on new checking accounts at Fair Sav…

A: A trend line is a finest fit straight-line cast-off through liner data sets which support to…

Q: What th ree methods are used to determine the accuracy of any given forecasting method? How would…

Q: a) Forecast the demand for the week of October 12 using a 3-week moving average. b) Use a 3-week…

A: Forecasting is the process of estimating the future demand according to previous or historic…

Q: Consider the following time series. t 1 2 3 4 5 yt 6 11 9 14 15 (a) Choose the correct…

Q: Consider the following time series data: Week 1 2 3 4 5 6 Value 18 13 16 11 17…

A: Hi, We are supposed to answer 3 sub-parts at a time. Since you have not mentioned which subpart to…

Q: Marianne Kramer, the owner of Handy Man Rent-als, rents carpet cleaners to contractors and…

A: MAD stands for Mean Absolute deviation which is defined as average distance among every data value…

Q: Consider the data below which includes sales data and the forecasts that would have been made using…

A: Given data is

Q: The MAD for Method 1 = enter your response here thousand gallons (round your response to three…

A: Forecasting is a technique used to predict future outcomes on the basis of past data. In business…

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: An analyst must decide between two different forecasting techniques for weekly sales of roller…

A: Linear trend equation: Ft = 124 + 2.1t. When t = 11, forecast for the 11th period will be 124 + 2.1…

Q: What is the definition of a forecast error?a. The average difference between the forecast and the…

A: Forecasting is a tool that uses historical data as inputs that are predictive in deciding the path…

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: 4. What is the forecast for the 13th period based on the four-period moving average? Round your…

A: Given data is

Q: 1. The number of bushels of apples sold at a roadside fruit stand over a 12-day period were PROBLEMS…

A: Note: - Since we can answer only up to three subparts we will answer the first three subparts(1-a,…

Q: 6) 4 Consider the following time series data. Month 1 2 3 4 5 6…

A: Hi, we are supposed to answer 3 subparts at a time. Since you have not mentioned which subpart to…

Q: a) Forecast the number of disk drives to be made next year, using linear regression. b) Compute the…

A: Use the fax machine data to model the relationship between cumulative fax machines produced and…

Q: Consider the following time series data: Month Value 24 13 20 12 19 23 15 a.…

A: Given data is

Q: Air travel on Mountain Airlines for the past 18 weeks was:Week Passengers1 4052 4103 4204 4155 4126…

A: a) The moving average technique would not be appropriate for the given data because the data is…

Q: a. What is your forecast for December of Year 4, making period 1 as the starting period for the…

A: a) Period Demand Square of X Multiplication of x and y, XY 1 4507 1 4507 2 4400 4 8800…

Q: 1. Forecasting techniques e following set of data represents the quarterly changes in demand for an…

A: Below is the solution:-

Q: 13. Two forecasting methods have been used to evaluate the same economic time series. The results…

A: Formula:

Q: Consider the following time series data. Choose the correct time series plot. (i) (ii)…

A: A time series is a grouping of information focuses that happen in progressive requests throughout…

Q: a) Use a 2-month moving average on all the data and plot the averages and the prices. b) Use a…

A: The mean absolute deviation(MAD) shows the errors in the forecasted values from the actual values.…

Q: An analyst must decide between two different forecasting techniques for weekly sales of roller…

A: MAD stands for mean absolute deviation. Whereas, MSE stands for mean squared error. These are the…

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: 4.1 The following gives the number of pints of type A blood used at Woodlawn Hospital in the past 6…

A: Forecasting is the process of determining future sales with estimation using previous or historic…

Q: 9 438 18 482 a. Explain why an averaging technique would not be appropriate for forecasting. b. Use…

A: Forecasting is an important part of any business. It helps to predict future demand and production…

Q: Following are two weekly forecasts made by two different methods for the number of gallons of…

A: Given data:

Q: b) Use a 3-week weighted moving average, with weights of.1, .3, and .6, using.6 for the most recent…

A: Forecasting is the process of determining the estimated future demand using historical information…

Q: a. Compare a three-month moving average forecast with an exponential smoothing forecast. Use a =…

A: Below is the solution:-

Q: Gasoline sales Times Series week sales (1000s of gallons 1 17 2 21 3 19 4 23 5 18 6…

A: Formula:

Q: An analyst must decide between two different forecasting techniques for weekly sales of…

Q: The monthly sales for Yazici Batteries, Inc., wereas follows: a) Plot the monthly sales data.b)…

A: Since you have asked multiple questions, we will solve the first three parts for you (a, b) i, and…

Q: he monthly sales for Yazici Batteries, Inc., were as follows: Month Sales his exercise contains only…

A: Ans) In Naive forecasting, forecast is equal to previous demand. In 3 Month Moving Average forecast…

Q: 3. National Mixer, Inc., sells can openers. Monthly sales for a seven-month period were as follows:…

A: Note: - Since we can answer only up to three subparts we will answer the first three subparts (a, b…

Concept explainers

Forecasting in Business

Forecasting is the process of predicting the future based on the past and the present data and circumstances. In other words, forecasting is the act of making a detailed analysis of future events based on the decisions made in the past as well as the present. Forecasting plays a very important role in operational management as it helps in planning and decision-making. It is not only important for the success of a business but also contributes to individual growth and success. Many business organizations or companies have failed due to the shortcomings of their forecasting.

Question

14. Consider the following time series.
t
1
2
3
4
7
Yt
120
110
100
96
94
92
88
a. Construct a time series plot. What type of pattern exists in the data?
b. Develop the linear trend equation for this time series.
c. What is the forecast for t = 8?

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Step 1

VIEW

Step 2

VIEW

Step 3

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 3 steps with 6 images

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, operations-management and related others by exploring similar questions and additional content below.

Similar questions

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_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_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_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_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?
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_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 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?