QUESTION 4 The table below is used for Questions 4 and 5. It contains three estimated regressions, which were computed in 2007 using data on employees. The data set used for the regressions consisted of information on over 10,000 full-time, full-year workers. Employees were surveyed on their earnings and whether they had graduated high school or not. The data set also contains information on the region of the country where the person lived (North / East / South / West), and the individual's gender and age. For the purposes of this quiz: AHE = average hourly earnings Graduated high school (X1) = binary variable (1 if the employee graduated high school, O if they did not) Male (X2) = binary variable (1 if male, O if female) Age (X3) = age in years North (X4) = binary variable (1 if Region = North, 0 otherwise) South (X5) = binary variable (1 if Region = South, 0 otherwise) East (X6) = binary variable (1 if Region = East, 0 otherwise) Results of Regressions of Average Hourly Earnings on Gender and Education Binary Variables and Other Characteristics Using 2007 Data from the Current Population Survey Dependent variable: average hourly earnings (AHE). Regressor 1 3 0.373 (0.021) Graduated high school (X¡) 0.352 0.371 (0.021) (0.021) Male (X2) 0.451 (0.020) 0.458 0.457 (0.021) (0.020) Age (X3) 0.011 0.011 (0.001) (0.001) North (X4) 0.175 (0.37) South (Xs) 0.103 (0.033) East (X6) -0.102 (0.043) 12.84 (0.018) 12.471 (0.049) 12.390 (0.057) Intercept F-statistic for regional effects = 0 21.87 SER 1.026 1.023 1.020 R2 0.0710 0.0761 0.0814 10973 10973 10973 Using the regression results in column (1): Is the coefficient on "Graduated high school", estimated from this regression, statistically significant at the 5% level? The calculated test statistic is (two decimal places) Therefore, is the null hypothesis rejected at the 5% level of significance? (Type Yes or No)
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.
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