result conclusiony

result conclusiony - Model Summary(b) Model R R Square...

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Unformatted text preview: Model Summary(b) Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics Durbin-Watson R Square Change F Change df1 df2 Sig. F Change R Square Change F Change df1 df2 Sig. F Change 1 .911(a) .830 .788 .09060 .830 19.581 2 8 .001 1.149 a Predictors: (Constant), FDI, DR b Dependent Variable: GDP ANOVA(b) Model Sum of Squares df Mean Square F Sig. 1 Regression .321 2 .161 19.581 .001(a) Residual .066 8 .008 Total .387 10 a Predictors: (Constant), FDI, DR b Dependent Variable: GDP Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. Collinearity Statistics B Std. Error Beta Tolerance VIF B Std. Error 1 (Constant) 4.415 .474 9.312 .000 DR .461 .314 .217 1.468 .180 .975 1.026 FDI .381 .061 .920 6.239 .000 .975 1.026 a Dependent Variable: GDP REGRESSION EQUATION : We have analyzed data on SPSS software. The results are as follows Y (GDP) = 4.415 + 0.381 (FDI) + 0.461(DR) ESTIMATION AND RESULT: As vale of (R square) is 0.83 shows there is a strong relationship between DR, FDI, and GDP, therefore it is concluded i.e. FDI and DR has significant As vale of (R square) is 0....
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This note was uploaded on 06/30/2011 for the course ECO 4701 taught by Professor Ahmed during the Spring '11 term at Andhra University.

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result conclusiony - Model Summary(b) Model R R Square...

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