Using data from 50 clerical workers, a researcher estimates wage = Bo + ß1Education + B2Experience + B3Age + E, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. The regression results are shown in the following table. Standard Error Coefficients t Stat p-Value 0.0603 Intercept 7.90 4.09 1.93 Education 2.44 0.34 4.24 0.0001 Experience 0.54 0.14 3.16 0.0028 Age -0.02 0.08 -0.14 0.8920 What is the sample regression equation (round to 2 decimal places)? y3D Education + Experience + Age What is the hourly wage for a 30-year-old worker with 4 years of higher education and 3 years of experience (round to 2 decimal places)? Are any independent variables insignificant at a 95% level of significance? (Y/N)
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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