Regression Analysis - Statistics Project Example

The GDP of the UAE is the dependent variable, Y while the Exports and the imports of the UAE will be the dependent variables in the analysis (X1 and X2 respectively). The Pearson’s analysis of the relationship between the GDP and the Exports of the UAE (at 0.05 significant level) reveals that the Pearson’s correlation index, ρ=0.713. Comparing ρ (Correlation index) to the significance level formulated during the analysis reveals that ρ˃0.05. This infers that the correlation is not statistically significant.

The statistical inference that can be made from the data used in this study thus reveals that the fact that imports in UAE have a positive relationship with the GDP occurred simply by chance. The sample data used in the reflection of the GDP of the country versus the indices of the experts do not reflect the occurrence when the whole “population data” was used. At a statistical level of 0.05, the analysis of the two variants, the GDP, and the imports of UAE reveals that ρ is greater than the significance level, 0.05. When ρ˃ 0.

05 (Statistical significance level) it infers that the correlation between the two variables is not statistically significant. This assertion means that the observation from the samples analyzed (the data from World Development Index) does not explicitly outline the relationship between the imports of the UAE and the GDP of the UAE. The multiple regression analysis estimates the coefficients of the linear equation especially in the cases where more than one independent variable exists.