# problem solving

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Assignment 2 Introduction to Econometrics STATA OUTPUT – For a The sample mean for beauty ratings is -0.0109287, as shown from the output. STATA OUTPUT – Q b The regression output predicts course evaluation using beauty, with beauty being the independent variable while the course evaluation is the dependent variable. From the output the null hypothesis from the F-test is that the R-squared is 0, but the F-test value is 0.0085 which is less than 0.05, therefore we reject the null hypothesis with 95% level of confidence. The R-squared, 0.0197 shows that the model explains only 1.97% of the variation in course evaluation is explained by the model, because the model does not explain 98.03%, we can conclude that it is a worse model. The t-test for beauty has a p-value of 0.009, which is less than 0.05 therefore we can reject the null hypothesis at 95% confidence level and conclude that beauty has a significant effect on the course evaluation. The coefficients of the variables are 0.0983013 for beauty and 4.02936 for constant. This explains that for every unit increase in the beauty there is a significant increase in course evaluation by 0.0983013. The correlation between beauty and course evaluation is positive therefore any change in beauty will influence an increment on course evaluation. The coefficient for the constant at 4.02936 is the value of course evaluation when beauty is zero. The coefficient on beauty is significant at 5% level since it has a p-value that is less than 0.05. c. STATA OUTPUT –Q c We run the regression with option 1 of onecredit omitted, since we want an indicative variable with classes not single credit represented by

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