5. We estimate the following regression model to predict wage of employees in a firm. Exp is years of experience, male is a dummy variable that equals 1 if the employee is male. wage %3D Bo + Bјехр + Bzтale + Bзехр х тale If the true relationship between the variables are as the following plot suggests, what do you expect the signs (positive or negative) of B1, B2, and ß3 to be? Explain. wage + male=1 male=0
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.
![5. We estimate the following regression model to predict wage of employees in a firm. Exp is years of
experience, male is a dummy variable that equals 1 if the employee is male.
wage = Bo + Biexp + B2male + Bzexp × male
If the true relationship between the variables are as the following plot suggests, what do you expect
the signs (positive or negative) of B1, B2, and B3 to be? Explain.
wage
male=1
male=0
experience](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F4f8edec1-8d43-45b2-a95b-be2335431e6b%2F499fd268-3e82-44f2-8cf1-53d047aeb82a%2F78cyde7_processed.png&w=3840&q=75)
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