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 2032.20122014 2016 20182020CO2 Emissions 338.5 364.5 397.1 423.8 452.1 498.4Year2010Year2022 2024 2026 2028 2030CO2 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) =2032741.7(b) Find the model's estimate for the 2024 data point. (Round your answer to two decimal places.)million metric tonsInterpret 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 bymillion metric tons.

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Answered: The following table gives the millions…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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The prices of agricultural commodities for 1946-47 and for the inonth of Dece:mber 1950 are given below along with the value of the output of hese commodities in 1946-47: Value of outptl in million (Rs.) Prices ELIII Commodities Unit 1946-47 (Rs.) Dec. 1950 (Rs.) (1946-47) 13.75 9-70 8364 Rice Wheat Jowar maund таund 13-75 9.70 2207 6:03 8.00 876 maund 466 00 433.00 701 Cotton (raw) Tea Ibs. 1:25 1:75 534 Ibs. Calculate the weighted index mumber of prices of these commodities for December 1950 taking 1946-47 as base.
1.8 Compute and compare the total electricity consumption of Sub-Saharan Africa to the United States in 2012. The population of Sub-Saharan Africa was 926 million, and the United States was 314 million. The per person consumption in the United States in 2012 was 12.96 MWh per year. Consult Fig. 1.11 for the per person consumption in Sub-Saharan Africa.
Given this data estimate the population in 2060.
Table 1. DEMOGRAPHY OF COUNTRY X 2020 2018 2015 Total population 109,035,343 100,981,437 92,337,852 Average annual population growth rate 1.63 (2015- 2020) 1.72 (2010- 2015) 1.90 (2000- 2010) Population density (persons per square kilometer) 363 337 308 Births (Based on civil registration) Male 990,390 750,871 632,870 Female 952,126 972,802 487,798 Deaths (Based on civil registration) Timely 506,530 509,762 473,987 Late 106,820 110,382 116,803 2012 2009 2005 Total population by sex 102,303,977 93,114,333 89,088,544 Male 51,962,069 46,257,634 44,788,757 Female 50,341,908 46,856,699 44,299,787 Proportion of total population by sex Male 50.79 49.68 50.27 Female 49.21 50.32 49.73 Total population by age group 0-4 years 10,931,818 10,784,233 10,656,575 0-14 years 32,793,155 30,937,734…
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…
i. ii. Table 1 iii. Top 15 countries with the highest wind power Country iv. Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 China United States Germany United Kingdom India Brazil Spain France Canada Sweden Italy Turkey Australia Netherlands Mexico Gigawatt hours (GWh) 467037.4 341818.0 132102.0 75369.1 63522.3 57050.0 56444.0 39791.9 35638.0 27526.0 18676 14304 please solve iv only by minitabe 12080 10607 b. Construct a 95% confidence interval on the mean wind power. Calculate the sample mean and variance. Write the appropriate confidence formula and the assumptions. Calculate the confidence interval manually. Perform the analysis by Minitab. Copy your output and insert it into your report (use the latest Minitab version and do not write/type the output). 8951 7 4
5.8 Driving Safety Data How many miles does a car traveling at a mph cover in five hours? S

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