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primi sui motori con e-max

APPENDIX D

REGRESSION MODELS FOR MOTION SIMULATORS

Regression Model Analysis

The initial scatterplot for the number of motion simulators and the number of corresponding helicopters showed that linear, cubic and quadratic equations would describe the regression model with greater precision than the rest.

SPSS regression model
Figure 8. Scatterplot for number of motion simulators and number of helicopters.

Linear

The SPSS “curve estimation” analysis for the linear equation gave the results shown on tables 2, 3, and 4.

Table with the Linear Model Summary for Motion Simulators
Linear Model Summary for Motion Simulators
Table with the Analysis of Variance for Motion Simulators Linear Model
Analysis of Variance for Motion Simulators Linear Model
Table with the Coefficients for Motion Simulators Linear Model
Coefficients for Motion Simulators Linear Model

Quadratic

The SPSS “curve estimation” analysis for the quadratic equation gave the results shown on tables 5, 6, and 7.

Table with the Quadratic Model Summary for Motion Simulators
Quadratic Model Summary for Motion Simulators
Table with the Analysis of Variance for Motion Simulators Quadratic Model
Analysis of Variance for Motion Simulators Quadratic Model
Table with the Coefficients for Motion Simulators Quadratic Model
Coefficients for Motion Simulators Quadratic Model

Cubic

The SPSS “curve estimation” analysis for the quadratic equation gave the results shown on tables 8, 9, and 10.

Tables with the Quadratic Model Summary, Analysis of Variance and Coefficients for Motion Simulators
Tables with the Quadratic Model Summary, Analysis of Variance and Coefficients for Motion Simulators

Chosen Model

All three models indicated that there is a strong correlation between the number of helicopters and the corresponding simulators (.863<R2<.898). Figure D2 presents the curve fit of the three equations. Although the cubic equation had the best fit (R2=.898), it was rejected because it suggested that, after a number of helicopters, the number of simulators used should be growing at a growing rate.

SPSS regression model
Figure 9. Curve fit analysis for number of motion simulators and number of helicopters.
Figure 9

This can not be true, since higher number of simulators give more flexibility and thus better utilization of the available resources.

Between the other two models the quadratic had a higher R square value. It also presented a better fit for very high number of helicopters and thus it was chosen as the regression model to predict the number of simulators. The equation of the model is Y=0+(.024*X)-(4.9*10-006*X2).


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