2. In order to understand who smokes and who does not, we collected data on 1,193 individuals. For each individual, we measured: whether she smokes (SMOKER=1) or not (SMOKER=0); her age (in number of years); education (in number of years of education); income as of previous year; and the average cigarette prices in her city. For example, the first individual had the following measured variables: she was a smoker (SMOKER=1), was 35 years old (AGE=35), had 12 years years of education (EDUCATION=12), income of $65,000 (INCOME-65,000) and the average cigarette price in her city was $2.15 (CIGARETTE_PRICE=2.15). A logistic model on whether SMOKER=1 was run and the results are shown in Figure 2. Intercept AGE EDUCATION INCOME CIGARETTE PRICE # obs Coeff p-value (0.001) 2.740 -0.020 (0.000) -0.090 0.000 -0.002 1,193 (0.000) (0.516) (0.070) Figure 2: Logistic regression results Does education matter in determining the probability that someone becomes a smoker? Discuss the significance and the magnitude of the effect of education (through its influence on the odds of becoming a smoker).