Question

Use the CO2 data and via Multiple regression select the two variables that predict the CO2 level with the best P-value. Make another table with these two variables and answer the questions. Numerical answers are rounded so choose the answer that matches the best: Hour CO Traffic Wind 1 2.4 50 -0.2 2 1.7 26 0.0 3 1.4 16 0.0 4 1.2 10 0.0 5 1.2 12 0.1 6 2.0 41 -0.1 7 3.4 157 -0.1 8 5.8 276 -0.2 9 6.8 282 0.2 10 6.6 242 1.0 11 6.6 200 2.3 12 6.3 186 3.8 13 5.8 179 4.6 14 5.5 178 5.4 15 5.9 203 5.9 16 6.8 264 5.9 17 7.0 289 5.6 18 7.4 308 4.9 19 6.4 267 3.8 20 5.0 190 2.5 21 3.8 125 1.4 22 3.5 120 0.6 23 3.3 116 0.4 24 3.1 87 0.1 Answer the questions for Assessment: 13. What are the two selected variables? a. Hour and Traffic b. Wind and Traffic c. Hour and Wind 14. Which of the variables has a better P-value and what is this P-value? (Note: numbers are truncated.) a. Traffic; 0.018 b. Traffic; 6.85E-12 c. Wind; 0.0056 d. Wind; 0.174 15. Based on the table, how would you characterize the Regression fit? a. Poor b. Good c. Excellent 16. What is another name for the coefficient 1.274461 and what is its interpretation based on the data? a. The X-intercept; when the average weekday traffic density and the perpendicular wind-speed component are zero. b. The slope of an average summer weekday's CO2 concentration. It is how much the CO2 concentration will increase when both the average weekday traffic density and the perpendicular wind-speed component increase by 1 unit. c. The Y-intercept; It is how much the CO2 concentration will increase when both the average weekday traffic density and the perpendicular wind-speed component are zero. d. The Y-intercept; it is the average summer weekday CO2 concentration when the average weekday traffic density and the perpendicular wind-speed component are zero. e. None of these

Answer 1

13. What are the two selected variables? b. Wind and Traffic

14. Which of the variables has a better P-value and what is this P-value? (Note: numbers are truncated.) b. Traffic; 6.85E-12

15. Based on the table, how would you characterize the Regression fit? c. Excellent

16. What is another name for the coefficient 1.274461 and what is its interpretation based on the data?

c. The Y-intercept; It is how much the CO2 concentration will increase when both the average weekday traffic density and the perpendicular wind-speed component are zero.