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Of the four independent projection methodologies, two utilize one basic analytical tool, regression analysis. The term regression analysis refers to the statistical technique by which estimates are made of the values of a dependent variables based on knowledge of the values of one or more other variables, called independent variables. For the socioeconomic regression in this analysis, the dependent variable was the appropriate airport activity figure, such as registered aircraft, while the independent variable was a socioeconomic factor, such as population. The historical trend analysis fitted historical data to classical growth curves and extends the demand element into future periods by regression analysis. The procedure for this analysis resembled the socioeconomic regression, except that time was substituted as the independent variable. The most common growth curves are in the form of linear, exponential or logarithmic equations. For this study, the equational form of the projection line most often developed was linear. To measure the relationship between dependent and independent variables in both the regression and the trend analysis, the coefficient of determination (R') and the standard error of the estimate (y) were used. The RZ statistic indicates whether the given independent variable might be related to the dependent variable. It does so by quantifying the percentage of the dependent variable's variation about its arithmetic mean that is explained by the model. For instance, an R' of 0.80 indicates that 80 percent of the variance that existed around the dependent variable's mean has now been explained by examining the variance around the regression line (i.e., only 20 percent of the variance that once existed still exists). The socioeconomic regression and historical trend analysis methodologies were used to project the number of registered aircraft in the Twin Cities metropolitan area; the results are shown in Table II-i. Analysis of historical per capita ownership ratios revealed that these ratios were relatively constant at approximately 0.00129 aircraft per person in the metropolitan area during the years 1984 through 1987. The number of registered aircraft i the metropolitan area decreased in 1988, and the per capita ratio declined as well. In projecting registered aircraft under the per capita ownership methodology, it was assumed that the resurgence II-3