coefficient
|
A coefficient is a numerical expression which is multiplied with the value of a variable
|
conditional expectation function
|
see Population Regression Function (PRF)
|
error term
|
The error term quantifies the distance between each observation and the corresponding point on the regression line. The terms are denoted as ϵi
|
intercept
|
The intercept is the point at which the regression line intersects the y-axis. In this book we denote it as β0
|
Ordinary Least Squares
|
The method of fitting a regression line by means of minimizing the sum of the squared distances between the observations and the estimated values
|
Population Regression Function
|
The Population Regression Function (PRF) describes the expected distribution of y, given the values of the independent variable(s) x. It is also called the conditional expectation function (CEF) and can be denoted as E(yi|xi)
|
regression
|
Regression analysis determines the direction and magnitude of influence of one or more independent variables on a dependent variable
|
regression line
|
The regression line describes how the dependent variable is functionally related to the values of the independent variable. It it defined by the intercept β0 and the slope β1
|
residual
|
An estimation of the error term. The difference between an observation yi and the estimated value ˆyi. Denoted as ˆϵi
|
Sample Regression Function
|
A regression line based on a randomly drawn sample
|
slope
|
A slope is defined as rise over run, and so it tells us how many units of y we need to climb (or descend if the slope is negative) for every additional unit of the independent variable x
|