Fit a parabolic trend to the following time-series data and estimate theproduction in 2022 :Year2011201220132014201520162017Production(in '000 units):42.49627592122158

The equation is y=a+bx+cx2 and the normal equations are

Answered: Fit a parabolic trend to the following…

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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The following table gives the millions of metric tons of carbon dioxide emissions in a certain country for selected years from 2010 and projected to 2032. 2012 2014 2016 2018 2020 CO2 Emissions 338.5 364.5 397.1 423.8 452.1 498.4 Year 2010 Year 2022 2024 2026 2028 2030 CO2 Emissions 557.2 592.9 628.7 662.1 707.1 (a) Create a linear function that models these data, with x as the number of years past 2010 and y as the millions of metric tons of carbon dioxide emissions. (Round all numerical values to two decimal places.) y(x) = 2032 741.7 (b) Find the model's estimate for the 2024 data point. (Round your answer to two decimal places.) million metric tons Interpret the slope of the linear model. For each year since ---Select--- (c) Find the slope of the linear model. (Round your answer to two decimal places.) , carbon dioxide emissions in the U.S. are expected to change by million metric tons.
b. Use a = 0.2 to compute the exponential smoothing forecasts for the time series (to 2 decimals). Time-Series Value Month Forecast 1 110 2 130 120 4 110 5 95 6. 125 7 140 8 140 9 105 10 80 11 100 12 110 13
Q. 2 Describe the method of Moving averages for estimating the trend in a time series
Q. 14 Explain the Graphic method of trend estimation in a time series and give its merits and demerits.
the following information, Find the forecast for period two using exponential smoothing and a = 0.3. Period 2 Demand 64 70 A Forecast 59
Consider the plot of the total number E of Ebola cases in West Africa reported to the Centers for Disease Control and Prevention from April 1, 2014, through December 1, 2015. D +|+|||||||||||||||| ► Ebola Cases in West Africa E = A logistic fit for these data is given by 27,841.42 1 + 134.65-0.646 where t is the time in months since April 1, 2014. Below, we have added the graph of this model. +-+|||||||||||||||||| ► Logistic Graph Added (a) Does the first plot, "Ebola Cases in West Africa," show a continuing epidemic or a health crisis that is under control by December 2015? Because the data points appear to be [leveling off ✔✔✔, they show a health crisis that is under control (b) According to the model, what was the total number of cases when the disease was spreading at the fastest rate? Round your answer to the nearest whole number. 27021.61 x cases (c) Use the crossing-graphs method to determine when the disease was growing at the fastest rate. Round your answer, in months after…
The amount of time an individual will live in their current residence before moving to a new one follows an Exponential distribution. Assume that the mean time between moves is five years. Estimate the decay rate: A = What proportion of individuals will move within the next year, rounded to four digits?
Nitrogen dioxide, NO₂, is an air pollutant resulting from burning fossil fuels in cars and power plants. The following table shows the decrease in the national average of the concentration in parts per billion (ppb) of NO₂ for selected years. Year 2014 40.8107 2015 2016 2017 2018 39.7886 38.7972 37.8209 36.8752 NO₂ (ppb) Use exponential regression to find an exponential decay function for the concentration, C, of NO₂ t years after 2014. Round constants to the nearest ten-thousandth. c-40.8114 (0.9750) Use the model to predict the concentration of NO₂ (in ppb) in 2045. Round to the nearest whole number. 21 x ppb
The trend equation for a time series is fitted as Y. Shift the trend origin from 1998 to 1993, given that the time unit is 1 year. = 60 + 1.5X
Nitrogen dioxide, NO2, is an air pollutant resulting from burning fossil fuels in cars and power plants. The following table shows the decrease in the national average of the concentration in parts per billion (ppb) of NO2 for selected years. Year 2014 2015 2016 2017 2018 NO2 (ppb) 40.8107 39.7886 38.7972 37.8209 36.8752 Use exponential regression to find an exponential decay function for the concentration, C, of NO2 t years after 2014. Round constants to the nearest ten-thousandth. C = Use the model to predict the concentration of NO2 (in ppb) in 2050. Round to the nearest whole number. ? ppb
Consider the following table that gives the population of City A from Year 1 to Year 6. Complete all parts (a-k) to this question. Part 1: Fill-in the last two columns in the table. List your answers as a - j for the chart and answer the question k below. Round growth rate to the nearest ten-thousandth (4 decimal places). Population of City A, Year 1 to year 6 Year Population (P) Change ΔP{"version":"1.1","math":"<math xmlns="http://www.w3.org/1998/Math/MathML"><mo>∆</mo><mi>P</mi></math>"} Growth Rate ΔPP{"version":"1.1","math":"<math xmlns="http://www.w3.org/1998/Math/MathML"><mfrac><mrow><mo>∆</mo><mi>P</mi></mrow><mi>P</mi></mfrac></math>"} 1 315,422 N/A N/A 2 320,421 a. b. 3 321,765 c. d. 4 322,162 e. f. 5 331,165 g. h. 6 331,200 i. j. Part 2: k. Does it make sense to fit this data with an exponential model? Why or why…

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Fit a parabolic trend to the following time-series data and estimate the production in 2022 : Year : 2011 2012 2013 2014 2015 2016 2017 Production 42. 49 62 75 92 122 158 (in '000 units)