a. What is the interpretation of the educationand dself coefficients? Are these twocoefficients individually significant? (Note: use a significance level of 1 percent.) b. What is the interpretation of the experience coefficients? What is the marginal effect of experienceon lnearnings? c. Is the marginal effect of experienceon lnearnings diminishing? Or is it constant?Write down the null and alternative hypotheses and all the other relevant steps of this test. What do you conclude? (Note: use a significance level of 1 percent.) d. What are the predicted lnearnings for someone with 10 years of education and the following characteristics? Fill in the fo llo wing table and provide the working outs. 10 years of experience 20 years of experience self- employed non-self employed e. We want to investigate if education and experience (and its square) jointly have any effect on lnearnings. Write down the null and alternative hypotheses of this test. What are the degrees of freedom associated with this test? f.For the test in part (e), what is the critical value associated with a significance level of 1 percent? Briefly explain how you obtain this result
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
a. What is the interpretation of the educationand dself coefficients? Are these twocoefficients individually significant? (Note: use a significance level of 1 percent.)
b. What is the interpretation of the experience coefficients? What is the marginal effect of experienceon lnearnings?
c. Is the marginal effect of experienceon lnearnings diminishing? Or is it constant?Write down the null and alternative hypotheses and all the other relevant steps of this test. What do you conclude? (Note: use a significance level of 1 percent.)
d. What are the predicted lnearnings for someone with 10 years of education and the following characteristics? Fill in the fo llo wing table and provide the working outs.
| 10 years of experience | 20 years of experience | |
| self- employed | ||
| non-self employed |
e. We want to investigate if education and experience (and its square) jointly have any effect on lnearnings. Write down the null and alternative hypotheses of this test. What are the degrees of freedom associated with this test?
f.For the test in part (e), what is the critical value associated with a significance level of 1 percent? Briefly explain how you obtain this result
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