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- Simple Trend Analysis In this analysis, historical data on based aircraft (from 1951 through 1984) were used and the average annual growth rate was estimated. The number of based aircraft during the forecast period (1983-2010) was assumed to grow at the average annual growth rate and projections were made. The results indicated that there will be approximately 3175 aircraft in the region by 20!0, The average annual growth rate was 1.01%. - Continuation of Current Aircraft Ownership Levels In this method, the total number of aircraft per every 10,000 people in each community was estimated and this figure was used in projecting the number of aircraft for the community based on. its projected population in 2010. However, the results indicated an increase of 47% in total number of aircraft for the whole region, to a total of 3750. This forecast does not relate well to the trends considered, and was considered to be inaccurate. - Multiple Regression Analysis In this analysis, the number of aircraft owned by each community is related to its socio-economic and demographic characteristics. The 1983 Aircraft Registration file was sorted and aircraft were allocated to communities based on their owner's address, in 160 communities in the region. The socio-economic and demographic information for these communities were collected from the Council records for the years 1980 and 2010. The first step in the model building process was to correlate each of the socl economic variable (ex: population, employment, household in upper and higher income quartile,.etc.) to the number of aircraft owned by the community and choose the variables which had the highest correlation. The analysis showed that total population, households in upper and higher income quartiles, employment related to transportation, utilities, communication, business and financial services had very high correlation. A regression model using a standard statistical computer package was developed. Two models were developed - one for single engine aircraft and another for turbo props/jets. Since 160 data points were used in building the model, most of the variation in aircraft ownership levels were captured by the model. The model estimates that 3217 aircraft will be based in the region by t~e year 2010. Since model most accurately reflects the changing role of business aviation, and because the results were only about t percent different than those estimated by the trend analysis, the regression equation was adopted as the most likely forecast. Table 1 shows the results of that model.