A. Bivariate Analysis1. Choose and briefly discuss two (2) bivariate economic models of your choice. 2. From appropriate data websites, retrieve data ranging between 10 to 20 years, on the variables identified in the two (2) economic models of choice. 3. Use graphs and/or tables to express and represent the descriptive statistics for the variables of each of your economic models. 4. Express and explain, with the use of scatterplots the appropriate economic relationship for each economic model. 5. For each model, estimate the impact of the independent variable on the dependent variable by running a linear regression in Microsoft Excel. Write your estimated equation in mathematical form. 6. Using Microsoft Excel, calculate the standard errors of a, b and c, R-squared, degrees of freedom and the t-statistics for b & c for each model. 7. Interpret the coefficients of each economic model chosen. 8. For each economic model, determine and discuss whether the independent variable is statistically significant in explaining the dependent variable.
A. Bivariate Analysis
1. Choose and briefly discuss two (2) bivariate economic models of your choice.
2. From appropriate data websites, retrieve data ranging between 10 to 20 years, on the
variables identified in the two (2) economic models of choice.
3. Use graphs and/or tables to express and represent the descriptive statistics for the
variables of each of your economic models.
4. Express and explain, with the use of scatterplots the appropriate economic relationship
for each economic model.
5. For each model, estimate the impact of the independent variable on the dependent
variable by running a linear regression in Microsoft Excel. Write your estimated equation
in mathematical form.
6. Using Microsoft Excel, calculate the standard errors of a, b and c, R-squared, degrees of
freedom and the t-statistics for b & c for each model.
7. Interpret the coefficients of each economic model chosen.
8. For each economic model, determine and discuss whether the independent variable is
statistically significant in explaining the dependent variable.
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