The following scatterplot shows the mean annual carbon dioxide (CO2 ) in parts per million (ppm) measured at the top of a mountain and the mean annual air temperature over both land and sea across the globe, in degrees Celsius (C). Complete parts a through h on the right 2 16.800- - X - X Residual plot Regression output 2 16.650- Mean Temperature ( 16.575 16.500+ A regression predicting mean temperature from CO2 produces the 325.0 337.5 350.0 362.5 0.075 + following output table. CO2 (ppm) Residuals 0.000+ Dependent variable is: Temperature Click here to view the regression output. R-squared = 33.7% Click here to view the residual plot. -0.075 Variable Coefficient Intercept 15.305 325.0 337.5 350.0 CO2 0.004 CO2 (ppm)a) What is the correlation between CO2 and Temperature? e) What is the meaning of the y-intercept of this equation? O A. When the global mean temperature is 0 C, the CO2 level is 15.305 ppm. (Round to three decimal places as needed.) O B. For every 1 ppm increase in CO2 levels, the mean temperature increases by 0.004 C. b) Explain the meaning of R-squared in this context. O C. When the CO2 level is 0 ppm, the global mean temperature will be 15.305 C. O A. A linear model on CO2 levels accounts for 66.3% of the variation in mean temperature. O D. The y-intercept does not have a meaningful interpretation in the context of this problem. O B. A linear model on mean temperature accounts for 33.7% of the variation in CO, levels. () View the accompanying scatterplot of the residuals vs. CO2. Does the scatterplot of the residuals vs. CO2 show O C. A linear model on CO2 levels accounts for 33.7% of the variation in mean temperature. evidence of the violation of any assumptions behind the regression? O D. A linear model on mean temperature accounts for 66.3% of the variation in CO2 levels. O A. Yes, the equal variance assumption is violated. c) Give the regression equation. O B. No, all assumptions are okay. Using the provided regression output, the equation is Temp =+co2. O C. Yes, the linearity and equal variance assumptions are violated. (Type integers or decimals. Do not round. O D. Yes, the linearity assumption is violated O E. Yes, all the assumptions are violated d) What is the meaning of the slope of this equation? O F. Yes, the outlier condition is violated. O A. For every degree that the mean temperature increases, CO2 levels increase by 0.004 ppm. g) Suppose CO2 levels reach 364 ppm this year. What mean temperature does the regression predict from this O B. For every 0.004 ppm increase in CO2 levels, the mean temperature increases by 1 C. information? O C. For every 1 ppm increase in CO2 levels, the mean temperature increases by 0.004C. (Round to three decimal places as needed.) O D. The slope does not have a meaningful interpretation in the context of this problem. h) Does the answer is part g mean that when CO2 levels hit 364 ppm, the temperature will reach the predicted level? Explain briefly. O A. No. The actual temperature will be 15.305C. O B. No. The actual temperature will be significantly higher than the predicted level. O C. Yes. The temperature will reach the predicted level when CO, levels hit 364 ppm. O D. No. The actual temperature is likely to be different than the predicted level