ACADEMIA DE STUDII ECONOMICE DIN MOLDOVA Departamentul "Econometrie şi Statistică Economică" a. IV only b. I and IV, only Test nb.1 on Econometrics Variant 11 1. The aim of regression analysis ..... 2. Which of the following null hypothesis can be tested using an F-test? 1. b2=0 2. bl^2 3. b1 b2-b3^2=b4=0 4. bl-b2-b3-b4 c. I, III and IV, only d. None of the above APROB: Şef departamentul ofesor univ. 1. Pârţachi 3. Complete the table ANOVA knowing that total sum of squared deviations is equals 104, explained sum of squared is equals 89, number of observations = 52; the model is Y-bl+ b2X1 + b3X2+b3*X3 (1,5) 4. Solve the problem (6,0): Using the following values: sum squared of deviations on variable X equals 80, sum squared of deviations on variable Y equals 30; sum of product of deviations between the variables X and Y equals -40; arithmetic mean for variable X equals 6, arithmetic mean for variable Y equals 20. Number of observations 14. X pr=5 Estimate the coefficients: intercept and slope. Compute the table ANOVA and determine the coefficient of determination. Calculate the standard error on the estimated equation. Make the tests on statistical significance for level of significance 0,05 (t-test, F-test). List all levels of significance for which the null hypothesis is rejected. Calculate the pointed forecasting and confidence intervals. Calculate the average coefficient of elasticity; interpretation. Write a general conclusion about the quality of fitting the estimated equation.

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ACADEMIA DE STUDII ECONOMICE DIN MOLDOVA
Departamentul "Econometrie şi Statistică Economică"
Test nb. 1 on Econometrics
Variant 11
APROB: Şef departamentul
ofesor univ. 1. Pârţachi
1. The aim of regression analysis .....
2. Which of the following null hypothesis can be tested using an F-test?
1. b2 = 0
2. bl^2
3. b1 b2-b3^2=b4=0
4. bl-b2-b3-b4
a. IV only
b. I and IV, only
c. I, III and IV, only
d. None of the above
3. Complete the table ANOVA knowing that total sum of squared deviations is equals
104, explained sum of squared is equals 89, number of observations = 52;
the model is Y=b1+ b2*X1 + b3*X2+b3*X3 (1,5)
4. Solve the problem (6,0):
Using the following values: sum squared of deviations on variable X equals 80, sum
squared of deviations on variable Y equals 30;
sum of product of deviations between the variables X and Y equals -40;
arithmetic mean for variable X equals 6, arithmetic mean for variable Y equals 20.
Number of observations 14. X pr=5
Estimate the coefficients: intercept and slope. Compute the table ANOVA and determine
the coefficient of determination.
Calculate the standard error on the estimated equation. Make the tests on statistical
significance for level of significance 0,05 (t-test, F-test).
List all levels of significance for which the null hypothesis is rejected.
Calculate the pointed forecasting and confidence intervals. Calculate the average
coefficient of elasticity; interpretation. Write a general conclusion about the quality of
fitting the estimated equation.

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Regression analysis:

Regression analysis is specially a prediction process. In this prediction procedure, an independent variable or more than one independent variable participate. Also, a dependent variable takes part in this process.

While the researcher is using only one independent variable the regression model is called a bivariate regression model.

Also, if more than one variable are used to predict the response variable, then the regression is named as multivariate regression.