7.1: Linear Regression: Introduction

Question 1

Regression analysis is a tool for…

Answer 1

Examining whether a variable is useful for explaining another variable.

Question 2

Sum of squares total (SST) is the sum of…

Answer 2

Squared deviations of the dependent variable from its mean; the variation of the dependent variable.

*Also referred to as the total sum of squares.

Question 3

Dependent variable is the variable…

Answer 3

Whose variation about its mean is to be explained by the regression; the left-side variable in a regression equation.

*Also referred to as the explained variable. It is typically denoted by Y.

Question 4

Independent variable is a variable…

Answer 4

Used to explain the dependent variable in a regression; a right-side variable in a regression equation.

*Also referred to as the explanatory variable. Denoted by X.

Question 5

Simple linear regression (SLR) is a regression…

Answer 5

That summarizes the relation between the dependent variable and a single independent variable.

Question 6

Intercept is the expected value of…

Answer 6

The dependent variable when the independent variable in a simple linear regression is equal to zero.

Question 7

Coefficient in a SLR is the coefficient of…

Answer 7

An independent variable that represents the average change in the dependent variable for a one-unit change in the independent variable.

Question 8

Error term is the difference between…

Answer 8

An observation and its expected value, where the expected value is based on the true underlying population relation between the dependent and independent variables.

*Also known simply as the error.

Question 9

The linear relation between the dependent and independent variables is described as (formula):

Answer 9

Yi = b0 + b1Xi + εi, i = 1, . . . , n.

Question 10

Assumptions of the Simple Linear Regression Model include:

Answer 10

1 - Linearity

2 - Homoskedasticity

3 - Independence

4 - Normality