Читать книгу Business Experiments with R - B. D. McCullough - Страница 17

Run the above simple regression. You should get the same coefficients and standard errors.

A better analysis would add more variables to the regression to “control” for other factors. So, let's try adding other variables that we expect to drive life expectancy: LHB (natural logarithm of the number of hospital beds per 1000 in the country), LP (natural logarithm of the number of physicians per 1000 in the country), IS (an index of improvements in sanitation), and IW (an index of improvements in water supply). Since we don't believe that newspapers cause longer life expectancy, we would expect that once we include these variables in the regression, the coefficient on LN will be reduced. The results are

(1.2)

The coefficient on LN has not gone to zero; in fact, it hasn't changed much. The coefficients on all but one of the other variables that we know affect life expectancy are insignificant. What are we to make of this?