You have obtained measurements of height (in inches) of 29 female and 81 male students (Studenth) at your university. An estimated regression of this height on a constant and the following binary variables is indicated below: (BFemale) which takes a value of one for females and is zero otherwise, (BMale) which takes a value of one for males and is zero otherwise, Estimated(Studenth) = 71.0 - 4.84(BFemme).R = 0.40, SER = 2.0 Standard errors are as here: SE(intercept) = (0.3) SE(BFemme) = (0.57)
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) Is it likely that the error term is homoskedastic in here? Briefly explain.
(B) Suppose that an you modified this regression with two binary variables of female and male on the same equation. Can you run this regression? what problem would you run into?
Trending now
This is a popular solution!
Step by step
Solved in 2 steps
