Two-Variable Regression Model Flashcards
Define: Linear regression model
a model that is linear in the parameters, the B’s.
Define: Regression Analysis
the study of the relationship between one variable called the explained, or dependent, variable and one or more other variables called independent, or explanatory, variables.
Define: Dependent variable
Define: Independent variable
Define: Population Regression Line
a line that passes through the conditional means of Y
Define: Error term
It is a proxy for all the omitted or neglected variables that affect the dependent variable Y. The individual influence of each of these variables is random and small so that on average their influence on Y is zero.
Define: Residuals
Represents the difference between the actual Y values and their estimated values from the sample regression.
Define: Regression coefficients
The B coefficients in a linear regression model.
Define: Ordinary Least Squares (OLS) estimators
b1 and b2 should be chosen in such a
way that the residual sum of squares (RSS) is small as possible.
Name the objectives of regression analysis
Estimate the mean of a dependent variable given the values of the independent variables.
To test hypotheses about the nature of the dependence (hypotheses suggested by the underlying economic theory)
Forecast/ predict the mean value of the dependent variable given the values of the independent variables beyond the sample range.
Distinguish between: Regression analysis and Causation
Regression analysis - The study of the relationship between a dependent (explained) variable and other independent (explanatory) variables.
Causation - it does not necessarily mean that the independent variables are the cause, and the dependent variable is the effect.
Distinguish between: Deterministic and Stochastic components of the regression function
Deterministic component - mean or average value in the ith population
Stochastic component - non-systematic or random component.
Explain why there is an error term
Explain: The nature of the stochastic error term
Captures the influence of omitted variables.
Reflects the inherent randomness of human behaviour.
Errors of measurement
Simplicity: “do more with less”
Explain: How the sample regression function is an approximation of the population regression function
