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MANAGERIAL REPORT
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MANAGERIAL REPORT
INTRODUCTION The purpose of this analysis was to develop a regression model to predict mortality. Data was collected, by researchers at General Motors, on 60 U.S. Standard Metropolitan Statistical Areas (SMSA’s), in a study of whether air pollution contributes to mortality. This data was obtained and randomly sorted into two even groups of 30 cities. A regression model to predict mortality was build from the first set of data and validated from the second set of data. BODYThe following data was found to be the key drivers in the model: • Mean July temperature in the city (degrees F) • Mean relative humidity of the city • Median education • Percent of white collar workers • Median income • Suffer dioxide pollution potentialThe objective in this analysis was to find the line on a graph, using the variables mentioned above, for which the squared deviations between the observed and predicted values of mortality are smaller than for any other straight line model, assuming the differences between the observed and predicted values of mortality are zero. Once found, this “Least Squared Line” can be used to estimate mortality given any value of above data or predict mortality for any value of above data. Each of the key data elements was checked for a bell shaped symmetry about the mean, the linear (straight line) nature of the data when graphed and equal squares of deviations of measurements about the mean (variance). After determining whether to ex...
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