Chapter 4 - Regression Analysis

Question 1

What is a causal inference?

Answer 1

When you use data to estimate the effect on an outcome of interest of an intervention that changes the value of another variable

Question 2

What is a prediction?

Answer 2

Using the observed value of a variable to predict the value of another

Question 3

What is the function of a population regression?

What does this function tell us?

Answer 3

E(Y I X) = β0 + β1 X

The expected value of our dependent variable (Y) given our input of the dependent variable (X)

Question 4

What are the parameters of a linear regression?

Answer 4

β0 = intercept
β1 = slope

Question 5

What is the equation for the linear regression model with a single regressor?

Answer 5

Yi = β0 + β1 Xi + μi

Yi = dependent variable/regressand
Xi = the independent/regressor
β0 + β1 X = the population regression line
β0 = intercept of the population regression line
β1 = slope of the population regression line
μi = the error term