Problem #1c:Calculate the measures of forecast accuracy (MAE, MSE, and MAPE) to determinewhich smoothing forecast [(a) or (b)] would be preferred. Problem #1b:Use a two-month weighted moving average to create a forecast for May, using theweights: 0.6 and 0.4 (largest weight is for the most recent data). Calculate theforecast errors associated the weighted moving average forecasts.MonthDemandJanuary18February23March20April16May???

Note: As per my policy i can answer only one question. kindly post the remaining questions. 1b) Given data month Demand January 18 February 23 March 20 April 16 May ??1b)

Answered: Problem #1b: Use a two-month weighted…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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3) U.S. Health care expenditures. Because the over-65 population is growing more rapidly in the next few decades health care spending is expected to increase significantly in the next few decades. The following table gives the projected US health care expenditure (in trillions) from 2008 to 2013 Year 2008 2009 2010 2011 2012 2012 Expenditure 2.34 2.47 2.57 2.70 2.85 3.02 a) Draw a scatter diagram for this data. Use “Years since 2008” on the x-axis. Make sure the scatter diagram includes all required elements (axes labels, title, and appropriate scale) b) Use the points for 2009 and 2011 to find an equation of a line modeling this situation c) Use linear regression to find an equation of a line modeling this situation d) Use the equation in b to predict expenditures in 2016 and do this again for the equation in part c. What is the absolute and percentage difference between the two equations (use the equation in c as the base equation in the % calculation) e) Now use…
The MAD for the forecast developed using a weighted 2-year moving average with weights of 0.350.35 and 0.650.65 is what?
Here are the data for the past 21 months for actual sales of a particular product: LAST YEAR THIS YEAR January 300 275 February 400 375 March 425 350 April 450 425 May 400 400 June 460 350 July 400 350 August 300 275 September 375 350 October 500 November 550 December 500 Develop a forecast for the fourth quarter using a three-quarter, weighted moving average. Weight the most recent quarter 0.5, the second most recent 0.25, and the third 0.25. Solve the problem using quarters, as opposed to forecasting separate months. Note: Round your answer to 2 decimal places.
Below, we see a snippet of a dataset that consists of 128 observations and 15 variables. We present two models describing the linear relationship between the BodyFat and other variables. Density BodyFat Age Weight Height Neck Chest Abdomen Hip Thigh Knee Ankle 1 1.0708 12.3 23 154.25 85.2 94.5 59.0 37.3 21.9 2 1.0853 6.1 22 173.25 83.0 98.7 58.7 37.3 3 1.0414 87.9 99.2 59.6 38.9 4 1.0751 86.4 101.2 5 1.0340 100.0 101.9 63.2 42.2 6 1.0502 94.4 107.8 66.0 42.0 23.4 24.0 67.75 36.2 93.1 72.25 38.5 93.6 25.3 22 154.00 66.25 34.0 95.8 10.4 26 184.75 72.25 37.4 101.8 28.7 24 184.25 71.25 34.4 97.3 20.9 24 210.25 74.75 39.0 104.5 60.1 37.3 22.8 24.0 25.6 Biceps Forearm Wrist 1 32.0 27.4 17.1 2 30.5 28.9 18.2 3 28.8 25.2 16.6 32.4 29.4 18.2 5 32.2 27.7 17.7 6 35.7 30.6 18.8 Analysis of Variance Table Model 1: x$BodyFat ~ x$Neck Model 2: x$BodyFat x$Neck + xSWeight + x$Height F Pr (>F) Res. Df RSS Df Sum of Sq 1 250 13348.1 2 248 9461.4 2 3886.7 50.939 < 2.2e-16 *** --- Signif. codes: 0***…
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4 pts Problem #1a: Use a two-month moving average to create a forecast for May. Calculate the forecast errors associated the moving average forecasts. Month Demand January 18 February 23 March 20 April 16 May ??? Edit View Insert Format Tools Table | в I U 12pt v Paragraph v MacBook Pro &
C8. According to the Pew Research Center (2015), recent immigrants are better educated than earlier immigrants to the United States. The change was attributed to the availability of better education in each region or country of origin. The percentage of immigrants 25 years of age and older who completed at least high school is reported in this table for 1970 to 2013. Write a statement describing the change over time in the percentage who completed at least a high school degree. 1970 1980 1990 2000 2013 Mexico 14 17 26 30 48 Other Central/South America 57 53 60 66 Asia 75 72 75 82 84 48 68 81 87 95 Europe 36 48 52 58 72 Caribbean 81 91 88 85 85 Africa Source: Pew Research Center, Modern Immigration Wave Brings 59 Million to U.S., Driving Population Growth and Change Through 2065, 2015. Retrieved from https://www.pewresearch.org/hispanic/2015/09/28/modern- immigration-wave-brings-59-million-to-u-s-driving-population-growth-and-change-through-2065/ 52
The forecasts generated by two forecasting methods and actual sales have been collected in the Microsoft Excel Online file attached. Use the Microsoft Excel Online file attached to develop forecast accuracy and answer the following questions. 1. What is the MAD, the MSE, the MAPE, the RSFE, and the tracking signal for each forecasting method? Do not round intermediate calculations. Round your answers to two decimal places. Use the minus sign to enter negative values, if any. 2. What can be concluded about the quality of the forecasts 2? Assume that the control limit for the tracking signal is ±3. The results indicate (bias or no bias) in the forecasts 2, and that the tracking signal (is not or is) within the control limits of ±3.
U.S. Civilian Labor Force (thousands) Year Labor Force Year Labor Force 2007 153,918 2012 155,628 2008 154,655 2013 155,151 2009 153,111 2014 156,238 2010 153,650 2015 157,957 2011 153,995 2016 159,640 1. Fit three trend models: linear, exponential, and quadratic. Which model would offer the most believable forecasts? 2. Make forecasts using the following fitted trend models for years 2017-2019. t Exponential 11 12 13
If a forecaster wanted to choose a forecasting model that avoided having a large forecasting error in any given period, which error metric should they use when evaluating their forecasting options? CFE O AFE MAD MAPE O MSE
In Table L-1, the total value of imports of Indonesian goods and services from China for the 2010-2019 period is reported on a quarterly basis. With this data you are asked to analyze it with the Trend model and Seasonal Index. Question: a. Calculate a moving average with the average period length of 4 or MA (4) [why four?] And put the results in a column. Beware of selecting the rows to place the average result. b. Calculate the moving average with the length of the average period is 2 from the data in column MA (4) and the result is given the symbol MA (2x4) and the result is placed in a column. Beware of selecting the rows to place the average result. c. Calculate the ratio to the Moving Average (Y / MA (2x4)) and place it in a new column! d. Calculate a seasonal index and interpret the results! e. Create a Deseasonalized data series and place it in a new column! f. Plot the Dessasonalized data series and read the long-term movement patterns of data! Remember that understanding of…
6. The annual population of Afghanistan is available in the global economy data set. a. Plot the data and comment on its features. Can you observe the effect of the Soviet- Afghan war? b. Fit a linear trend model and compare this to a piecewise linear trend model with knots at 1980 and 1989. c. Generate forecasts from these two models for the five years after the end of the data, and comment on the results.

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