Cigarette smoking and cancer have been linked. Assume the number of bladder cancer deaths (in deaths/100 thousand) and cigarette sales (in cigarettes/person) for 35 randomly selected countries are in the table below. X, cigarette sales (in cigarettes/person) 18.2 Y, the number of bladder cancer deaths (in deaths/100 thousand) a) State the random variables. 2.9 29.18 4.99 30.34 3.46 27.56 4.04 26.38 4.47 28.64 5.98 33.6 4.78 19.96 2.89 25.82 3.52 18.06 3.25 22.86 4.78 21.16 2.9 23.75 3.95 23.44 2.86 23.44 2.93 21.84 2.91 18.24 2.99 22.12 4.23 26.18 4.09 21.17 4.04 28.92 4.79 20.08 2.94 28.6 4.46 28.27 4.46 25.91 5.21 23.32 3.72 28.04 3.2 21.25 5.14 14 3.31 23.78 4.89 42.4 6.54 27.91 4.75 26.92 4.69 25.89 20.94 4.63 3.64 rv X= the cigarette sales rv Y the the number of bladder cancer deaths of a randomly selected country of a randomly selected country b) Make a scatterplot of X versus Y in StatCrunch (optional). Why do we wish to sketch a scatterplot? To verify that a linear model is appropriate and to look for outliers. c) Find the equation of the best-fitting line (the least squares regression equation). Round values to 4 decimal places. Include the restricted domain. equation: ? = * X restricted domain: cigarettes/person