Climate change 2016 Data collected from around the globe (including the sea ice data of Exercise 23) show that the earth is getting warmer. The generally accepted explanation relates climate change to an increase in atmospheric levels of carbon dioxide (CO,) because CO, is a greenhouse gas that traps the heat of the sun. A standard source of the mean annual CO, concentration in the atmosphere (parts per mil- lion) is measurements taken at the top of Mauna Loa in Hawaii (away from any local contaminants) and available at ftp://aftp.cmdl.noaa.gov/products/trends/ co2/co2_annmean_mlo.txt. Global temperature anomaly is the difference in mean global temperature relative to a base period of 981 to 2010 in °C. It is available at www.ncdc.noaa. gov/cag/data-info/global. Here are a scatterplot and regression for the years from 959 to 2016: 0.75 0.50 0.25 0.00 325 350 375 400 CO2 esponse variable is: Temp squared 89.7% = 0.0885 with 58 - 2 56 degrees of freedom ariable ntercept 02 Coefficient SE(Coeff) t-ratio -3.17933 P-value 0.1584 -20.1 <0.0001 0.00992 0.0004 22.1 <0.0001 ) Write the equation of the regression line. ) Is there evidence of an association between CO, level and global temperature? ) Do you think predictions made by this regression will be very accurate? Explain. ) Does this regression prove that increasing CO, levels are causing global warming? Discuss.
Climate change 2016 Data collected from around the globe (including the sea ice data of Exercise 23) show that the earth is getting warmer. The generally accepted explanation relates climate change to an increase in atmospheric levels of carbon dioxide (CO,) because CO, is a greenhouse gas that traps the heat of the sun. A standard source of the mean annual CO, concentration in the atmosphere (parts per mil- lion) is measurements taken at the top of Mauna Loa in Hawaii (away from any local contaminants) and available at ftp://aftp.cmdl.noaa.gov/products/trends/ co2/co2_annmean_mlo.txt. Global temperature anomaly is the difference in mean global temperature relative to a base period of 981 to 2010 in °C. It is available at www.ncdc.noaa. gov/cag/data-info/global. Here are a scatterplot and regression for the years from 959 to 2016: 0.75 0.50 0.25 0.00 325 350 375 400 CO2 esponse variable is: Temp squared 89.7% = 0.0885 with 58 - 2 56 degrees of freedom ariable ntercept 02 Coefficient SE(Coeff) t-ratio -3.17933 P-value 0.1584 -20.1 <0.0001 0.00992 0.0004 22.1 <0.0001 ) Write the equation of the regression line. ) Is there evidence of an association between CO, level and global temperature? ) Do you think predictions made by this regression will be very accurate? Explain. ) Does this regression prove that increasing CO, levels are causing global warming? Discuss.
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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Transcribed Image Text:38. Climate change 2016 Data collected from around the
globe (including the sea ice data of Exercise 23) show
that the earth is getting warmer. The generally
accepted explanation relates climate change to an
increase in atmospheric levels of carbon dioxide
(CO.) because CO, is a greenhouse gas that traps the
heat of the sun. A standard source of the mean annual
CO, concentration in the atmosphere (parts per mil-
lion) is measurements taken at the top of Mauna Loa
in Hawaii (away from any local contaminants) and
available at ftp://aftp.cmdl.noaa.gov/products/trends/
co2/co2_annmean_mlo.txt.
Global temperature anomaly is the difference in
mean global temperature relative to a base period of
1981 to 2010 in °C. It is available at www.ncdc.noaa.
gov/cag/data-info/global.
Here are a scatterplot and regression for the years from
1959 to 2016:
0.75
0.50
0.25
0.00
325
350
375
400
CO2
Response variable is: Temp
R squared = 89.7%
s = 0.0885 with 58- 2 56 degrees of freedom
Variable
Coefficient SE(Coeff)
t-ratio
P-value
Intercept
-3.17933
0.1584
-20.1
<0.0001
CO2
0.00992
0.0004
22.1
<0.0001
a) Write the equation of the regression line.
b) Is there evidence of an association between CO, level
and global temperature?
c) Do you think predictions made by this regression will
be very accurate? Explain.
d) Does this regression prove that increasing CO, levels
are causing global warming? Discuss.
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