In 2010, Scott Carrell, Marianne Page, and James West published a paper that uses econometrics in order to understand whether professor gender impacts student performance in math and science courses. The authors collected data on student grades in introductory courses taken between 2001-2008 for each of 9,015 students. I took some liberties in simplifying their results below. The following equation describes the performance of students in introductory math and science courses in terms of whether the professor is female or not (FemaleProfessor), whether the student is female or not (FemaleStudent), and an interaction variable between professor gender and student gender (FemaleStndent*FemaleProfessor). Performance is defined as a student's normalized grade in the course (this means you interpret changes in the performance variable in
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.
Suppose this regression suffers from heteroskedasticity. How would you adjust the model to account for it?
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