Suppose the number of cigarettes a person smokes in a day is our x variable and the number of times th cough in a day is the y variable. a) The number of cigarettes smoked in a day acts as the O correlation coefficient response variable O explanatory variable truc variable b) The number of coughs in a day acts as the O true variable O response variable explanatory variable O correlation coefficient Suppose that we have the following data: Cigarettes Z 5 7 9 3 Coughs 5 12 13 19 6 24 33 11 Z 10 11 52 68 20 6 24 30 8 3 2 15 5 1 c) Use StatCrunch to create a scatterplot. Looking at the scatterplot, is a linear regression appropriate for th data set? No, the data shows randomness. No, the data follows a curved line Instead of a straight line. Yes, the data seems to follow a linear trend. d) Use StatCrunch to find the equation of the regression line. What Is the slope? Round to 3 decimal places. c) What is the y Intercept? Round to 3 decimal places. f) What is the correlation coefficient? Round to 2 decimal places. g) What level of correlation strength does this correlation coefficient suggest between these variables? strong negative Omoderate negative moderate positive Oweak positive Ostrong positive Oweak negative h) What is the coefficient of determination, It Answer as a percent and round to 1 decimal place. 1) Which is the interpretation of this R 98.0% of the variability in the number of times a person coughs in a day is explained by the number of cigarettes they smoke. 98.0% of the variability in the number of cigarettes a person smokes in a day is explained by the number of times they cough in a day. About 0.980% of the variability in the number of cigarettes a person smakes in a day is explained by the number of times they cough in a day. 0.980% of the variability in the number of times a person coughs in a day is explained by the number of cigarettes they smoke. j) If a person smokes 30 cigarettes in a day, predict the number of times they will cough. Round to 3