POM 3430 Quiz 4

Year Quarter Revenue Q1 4.80 Q2 4.56 2015 Q3 4.88 Q4 4.91 Q1 5.37 Q2 4.99 2016 Q3 5.24 Q4 5.71 Q1 5.73 Q2 5.29 2017 Q3 5.66 Q4 5.70 Q1 6.07 Q2 6.03 2018 Q3 6.31 Q4 6.30 Q1 6.60 Q2 6.31 2019 Q3 6.82 Q4 6.75 Q1 7.10 Q2 6.00 2020 Q3 4.20 Q4 6.20

With a new chef and a creative menu, Café Venetian has witnessed a huge surge in sales. The following data show a portion of daily sales (in $) at Café Venetian in the first 100 days after the changes. Day Sales 1 226 2 185 100 1,737 pictureClick here for the Excel Data File a-1. Estimate the exponential trend model. (Negative values for regression coefficients should be indicated by a minus sign. Round your answers to 2 decimal places.) Predictor Variable Constant Day Coefficient 0.00 a-2. Use the estimated model to forecast for the 101st day. (Do not round coefficient estimates. Round final answer to 2 decimal places.) Forecast for the 101 day

Historical demand for Peeps is as displayed in the table. Month Demand January 11 February 18 March 31 April 39 May 44 June 53 July 67 August 82 September 96 Develop forecasts from June through October using these techniques: Holt's method with alpha=0.2 and beta=0.1. For Holt's model, the level and trend for May are assumed to be 44 and 12. Judge which forecast method is the best based on MAD.

Show with explanations and examples of the differences from trend analysis, cross sectional analysis, and industry comparables analysis.

Hi this question may have been posted before do not know just looking for assistance and having difficulties, the question comes from my online discussion forum post (SCMG 305 Global demand management)   Investigate the cause-and-effect relationships utilizing regression analysis, find one authoritative resource in the form of a U-tube video or Website that explains the use of regression analysis as a prediction model for forecasting. Try not to duplicate a resource already posted by another student. Insert a hyperlink for that resource so others may access it quickly. Finally, provide a quick short paragraph/summary explaining what you learned from the resource you provided strengthening your understanding of the use of regression analysis for forecasting.

Consumer expenditure plans is an example of a forecasting method. Which of the general categories best described this example?

You own a restaurant near the beach. Business has been growing each year, but obviously spikes during the summer months. A regression produces the following equation: M = 30,000 + 500t + 1,000S Where M is monthly sales, t is years past 2010, and S is a dummy variable for the summer months. If the month is June, July, or August, insert a "1"”. If not, the value for S is zero. What are the predicted sales for July 2020? Enter as a value.

You are given the actual sales volume for iPod, what used to be one of Apple’s popular electronic products. The data covers 12 years of sales data, from 2002 until 2014. Your task is to create a product life cycle graph for the iPod as shown on page 295 of the textbook. The product lifecycle is also available in the lecture slides for Chapter 9. Your life cycle graph should clearly identify the introduction, growth, maturity and declining stages for the iPod. You should show the unit sales in the vertical axis and the calendar years (i.e., time) in the horizontal axis. Once you create the product life cycle graph, answer the following questions:   Finally, explain why the iPod declined. You can use online sources to answer this questions. Again your answer should not be more that one paragraph of three to five sentences.

You are given the actual sales volume for iPod, what used to be one of Apple’s popular electronic products. The data covers 12 years of sales data, from 2002 until 2014. Your task is to create a product life cycle graph for the iPod as shown on page 295 of the textbook. The product lifecycle is also available in the lecture slides for Chapter 9. Your life cycle graph should clearly identify the introduction, growth, maturity and declining stages for the iPod. You should show the unit sales in the vertical axis and the calendar years (i.e., time) in the horizontal axis. Once you create the product life cycle graph, answer the following questions:   In which years did the maturity stage occurred for the iPod? Explain your reasons in one paragraph of three to five sentences long. In which years did the decline stage occurred for the iPod? Explain your reasons in one paragraph of three to five sentences long.

Name two coincident indicators used in forecasting

Forecast the average number of viewers during the 2009 season using a​ three-period weighted moving average with weights 3​, 2​, and 1​, applying 3 to the most recent data and 1 to the oldest data.

solve within 30 mins.

The following is the data of recent refrigerator sales at a local Home Depot store. Month  1  2  3  4  5Actual Sales  95  100  80  90  ???Inputs will be exact numbers. What is the forecasted sales in month 5 using naive approach.Please use a 2-month simple moving average method to forecast sales in month 5.Please use a weighted moving average method, with weights of 0.6 one period ago, 0.3 two periods ago, and 0.1 three periods ago, to forecast sales in month 5.

Choose one of the following forecasting methods discussed in this chapter: last-value, averaging, moving-average, or exponential smoothing.  Identify the conditions when the method is most appropriate to use and give an example of an application of this method.

In your company (electrical goods manufacturing), you want to forecast demand as well of a particular range of Smart TVs. Its monthly sales previous year, are presented in the table below: Month Sales January 400 February 650 March 1,150 April 1,700 May 500 June 900 July 1,150 August 1900 September 600 October 650 November 1,600 December 2050 Based on the above historical sales data: A) Create the corresponding graph and comment on the demand (sales) in terms of in trend, seasonality and periodicity please draw the diagram!!!!

A manager uses a trend equation plus quarterly relatives to predict demand. Quarter relatives are SR1 = 0.9, SR2 = 0.95, SR3 = 1.05, and SR4 = 1.1. The trend equation is: Ft = 11 + 3t. Over the past nine quarters, demand has been as follows: %3D Period, t: 1 4 7 8 9. Demand: 15 17 20 23 25 29 34 36 39 Click here for the Excel Data File Compute the MAD and tracking signal for each period. (Negative values should be indicated by a minus sign. Round your intermediate calculations and final answers to 3 decimal places.) Period, t Demand MAD Tracking signal 1 15 2 17 3 20 4 23 25 6. 29 7 34 36 39 LO

Two coincident indicators used in forecasting

Sediment buildup behind a dam can adversely affect a reservoir's storage capacity. Measurements of a reservoir in 1988 showed it had a capacity of 500,000 acre-feet of water. Measurements in 2018 showed that the reservoir's capacity has been decreasing at a rate of 2,000 acre-feet per year. Find a linear model of the number of acre-feet A of water in the reservoir n years after 1988.

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A researcher has a sample of 6 annual observations {94, 104, 102, 99, 111 and 107} for the CPI in country Z for the period 2015 to 2020, and wants to forecast CPI for the years 2021, 2022 and 2023. The researcher uses 3 different forecasting models: A, B and C. Model A is an AR(1) model with no drift and with an estimated autoregressive coefficient = 0.7. Model B is a MA(1) model with no constant and with an estimated MA coefficient = -0.4 (note the minus !). Model C is a random walk model with no drift. The error terms over the 2015-2020 period were estimated to have the values: {3, -1, 2, 4, -3, 1}.  a. Compute the 2021, 2022 and 2023 forecasted values for the consumer price index based on the three models. Show the formulas and the details of your calculations, and explain all the related symbols.  b. Suppose that the actual values of the CPI over the 2021, 2022 and 2023 were {108, 114, 105}. Calculate the Root mean square error of the three model forecasts over the 2021-2023…

The following gives the number of accidents that occurred on Florida State Highway 101 during the last 4​ months:     Jan    Feb    Mar    AprMonth    1    2    3    4Number of Accidents    30    40    70    105 Using the least-squares regression ​method, the trend equation for forecasting is ​(round your responses to two decimal ​places)​: y = ? + ?x

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