Question

Given the following Regression from an applied research which has three main variables DLRGDP –DRT-Trend interpret these results in an economic vision ( the tested variables significance , the model significance , the model Strength , the difference between R2 and ANOVA test , the relation between T-test and Probability )

Answer 1

ANSWER:

The variable DLRGDP is positively related with the dependent variable. When DLRGDP increases by 1 unit, the dependent variable increases by, on an average, by approximately 0.138 units. It is statistically significant at 5% significance level since the p-value ( = 0.0307) is less than 5% level of significance.

DRT variable is negatively related with the dependent variable. But this variable is not statistically significant as the p-value of 0.7915 is very high.

The TREND variable is also negatively related with the dependent variable and it is statistically significant at 5% signficance level.

The F-statistic of the overall model is 3.742232 and its probability value of 0.014556 is low. Hence, the model is overall significant.

The model's strength is estimated by the R² as it denotes the percentage of variation in the dependent variable explained by the explanatory variables in the model. The R² for this model is 13.02%.

An ANOVA test helps in finding out if an experiment's results is statistically significant or not. Basically, we test groups to see if there's any statistical difference between them. The R² on the other hand gives the total strength of the model and denotes the goodness of fit of the model.

The t-test gives the value of the t-statistic for a hypothesis testing. Hypothesis tests work by taking the observed test statistic from a sample and using the sampling distribution to calculate the probability of obtaining that test statistic if the null hypothesis is correct.

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