Fall 2003 • Name: _________________

The following data provides the number of infants who die before their first birthday by country. The per capita income for each country is also given. Think of the per capita income as being the total national income divided by the population. The per capita income is roughly the amount of money in the economy on a per person basis. Richer countries have higher per capita incomes.

Location Per Capita
in dollars
Infant Mortality
1000 live births
3300 11
CNMI 13100 38
Fiji 2000 17
FSM 1900 33
Guam 20700 7
Kiribati 600 55
1500 41
Nauru 9400 11
Palau 6400 17
Samoa 1300 33
Vanuatu 1276 63
  1. _________ Calculate the slope of the least squares line for the income and infant mortality data.
  2. _________ Calculate the y-intercept of the least squares line for the income and infant mortality data.
  3. _________ What does of the sign of the slope tell us about this data? That is, what type of correlation is this?
  4. _________ What is the predicted infant mortality rate for a nation with a per capita income of $5000.00?
  5. _________ What is the predicted per capita income for a nation with an infant mortality rate 20?
  6. _________ Calculate the linear correlation coefficient r for the income and infant mortality columns.
  7. _________ Is the correlation none, low, moderate, high, or perfect?
  8. _________ Calculate the coefficient of determination.
  9. __________________ What does the coefficient of determination tell us about the relationship between per capita income and infant mortality rates?
  10. __________________ Does the relationship appear to be a linear relationship between per capita income and infant mortality?
  11. __________________ Use Excel to try to determine what type of relationship might fit the data with a higher correlation coefficient.
  12. Based on the data above, would a college education improve the probability that your baby will survive and WHY? (Use back if necessary)
Linear Regression Statistics
Statistic or Parameter Symbol Equations Excel
Slope b   =SLOPE(y data, x data)
Intercept a   =INTERCEPT(y data, x data)
Correlation r   =CORREL(y data, x data)
Coefficient of Determination r2   =(CORREL(y data, x data))^2