In a Simple Regression Y = B0 + B1X Where

Multiple Choice

In a simple regression Y = b0 + b1X where Y = number of robberies in a city (thousands of robberies) ,X = size of the police force in a city (thousands of police) ,and n = 45 randomly chosen large U.S.cities in 2008,we would be least likely to see which problem?

A) Autocorrelated residuals (because this is time-series data)
B) Heteroscedastic residuals (because we are using totals uncorrected for city size)
C) Nonnormal residuals (because a few larger cities may skew the residuals)
D) High leverage for some observations (because some cities may be huge)