Regression analysis enables us to carry out the kinds of sophisticated analyses that might be undertaken by epidemiological researchers

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I . Regression analysis enables us to carry out the kinds of sophisticated analyses that might be undertaken by epidemiological researchers at places like the Centers for Disease Control or the World Health Organization. For our

final two analyses of health outcomes across nations, we will focus on the factors associated with life expectancy for

men. Although it might not seem directly related to health outcomes, a number of researchers believe that literacy is a critical factor in improving health. Citizens who can read are able to be much more effective consumers of health

information.

The SPSS output below presents a bivariate regression equation where “MaleLifeExp” is the dependent variable and

“Literacy” is the independent variable. The variable “Literacy”measures the percentage of people in each country who are able to read.

a. DependentVariabIe MaleLifeExp: Male Ufe Expectancy at Birth

b. Predictors (Constant, Literacy: Percentage ofAdults Mio Can Read CoefTIcies?

a. DependentVariable: MaleLifeExp: Male Life Expectancy at Birth 

A) Interpret both key components of the regression equation.

B) Is the slope coefficient in the regression equation  statistically significant (that is, using an alpha level of .05, can we reject a null hypothesis of no association)? Be sure to explain what information you use to determine whether the component is statistically significant or not.

C) Use the results of your regression results to predict the average malelife expectancy in a country ¡n which only 25% of the population can read. Compare this predicted value to the average male life expectancy in a country in which 85% of the population can read.

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