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global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 198 SUMMARY OUTPUT 19.6 Regression Statistics 19.4 Multiple R 0.51622776 19.2 R Square 0.2664911 19 Adjusted R Square 0.2175905 188 Standard Error 0.29668345 Observations 17 186 3.1 3.2 3.3 3.4 35 3.6 3.7 3.8 39 ANOVA df SS MS F ignificance F Regression 1 0.479683973 0.479684 5.44965 0.0338864 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Uper 95.0% 19.7831797 25.8195291 Intercept 22.8013544 1.416019771 16.10243 7.1E-11 19.78318 25.819529 0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247 -1.8353112 -0.08342469 Non-US -0.95936795 What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4? Oŷ = 22.8 – 0.96(3.4) Oy = 22.8(3.4) – 0.96 Oy = 22.8 – 0.96(3.4) Oŷ = 22.8(3.4) – 0.96 State the correlation value that best respresents the plot presented. O 0.516 O 0.266 -0.516 -0.266

global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 198 SUMMARY OUTPUT 19.6 Regression Statistics 19.4 Multiple R 0.51622776 19.2 R Square 0.2664911 19 Adjusted R Square 0.2175905 188 Standard Error 0.29668345 Observations 17 186 3.1 3.2 3.3 3.4 35 3.6 3.7 3.8 39 ANOVA df SS MS F ignificance F Regression 1 0.479683973 0.479684 5.44965 0.0338864 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Uper 95.0% 19.7831797 25.8195291 Intercept 22.8013544 1.416019771 16.10243 7.1E-11 19.78318 25.819529 0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247 -1.8353112 -0.08342469 Non-US -0.95936795 What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4? Oŷ = 22.8 – 0.96(3.4) Oy = 22.8(3.4) – 0.96 Oy = 22.8 – 0.96(3.4) Oŷ = 22.8(3.4) – 0.96 State the correlation value that best respresents the plot presented. O 0.516 O 0.266 -0.516 -0.266

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter10: Statistics
Section: Chapter Questions
Problem 25SGR
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Safari File Edit View History Bookmarks Window Help Wed 8:01 myopenmath.com МyOpenMath G What is the standard deviation of the data set comprising the numbers 3, 7, 4,... b My Questions | bartleby Carbon diOXiUE IS produCed by puing T0SSII TUETS SUCh as oit and laturar gas, ana Tlas pEen ConMEcted tO global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 19.8 SUMMARY OUTPUT 19.6 19.4 Regression Statistics Multiple R 0.51622776 19.2 R Square 0.2664911 19 Adjusted R Square 0.2175905 18.8 Standard Error 0.29668345 Observations 17 18.6 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 ANOVA df S MS ignificance F Regression 1 0.479683973 0.479684 5.44965 0.0338864 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 22.8013544 1.416019771 16.10243 7.1E-11 19.78318 25.819529 19.7831797 25.8195291 Non-US -0.95936795 0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247 -1.8353112 -0.08342469 What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4? O ŷ = 22.8 – 0.96(3.4) y = 22.8(3.4) – 0.96 Oy = 22.8 – 0.96(3.4) O ŷ = 22.8(3.4) – 0.96 State the correlation value that best respresents the plot presented. O 0.516 0.266 0.516 - 0.266 00
Transcribed Image Text:Safari File Edit View History Bookmarks Window Help Wed 8:01 myopenmath.com МyOpenMath G What is the standard deviation of the data set comprising the numbers 3, 7, 4,... b My Questions | bartleby Carbon diOXiUE IS produCed by puing T0SSII TUETS SUCh as oit and laturar gas, ana Tlas pEen ConMEcted tO global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 19.8 SUMMARY OUTPUT 19.6 19.4 Regression Statistics Multiple R 0.51622776 19.2 R Square 0.2664911 19 Adjusted R Square 0.2175905 18.8 Standard Error 0.29668345 Observations 17 18.6 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 ANOVA df S MS ignificance F Regression 1 0.479683973 0.479684 5.44965 0.0338864 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 22.8013544 1.416019771 16.10243 7.1E-11 19.78318 25.819529 19.7831797 25.8195291 Non-US -0.95936795 0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247 -1.8353112 -0.08342469 What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4? O ŷ = 22.8 – 0.96(3.4) y = 22.8(3.4) – 0.96 Oy = 22.8 – 0.96(3.4) O ŷ = 22.8(3.4) – 0.96 State the correlation value that best respresents the plot presented. O 0.516 0.266 0.516 - 0.266 00
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Given regression analysis

Statistics homework question answer, step 1, image 1

Predicted equation is given by

ŷ = 22.8 - 0.96(x)

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