Econ 103A: Practice Problems for Midterm 2

A collection of key vocabulary terms and their definitions related to the topics covered in the Econ 103A course and the midterm exam preparation.

Hypothesis Testing

A statistical method used to make decisions based on data, involving formulating a null hypothesis and an alternative hypothesis.

Multivariate OLS

Ordinary Least Squares regression that models the relationship between multiple independent variables and a dependent variable.

Dummy Variables

Binary variables used in regression analysis to represent categorical variables with two categories.

R-squared (R2)

A statistical measure that represents the proportion of variance for a dependent variable that's explained by independent variables in a regression model.

Perfect Collinearity

A situation where one independent variable is a perfect linear combination of other independent variables, causing issues in regression analysis.

Omitted Variable Bias

Bias that occurs in regression analysis when a relevant variable is excluded from the model.

Multicollinearity

The condition in which two or more independent variables in a regression model are highly correlated, potentially leading to inflated variance.

Degrees of Freedom

The number of independent values or quantities which can be assigned to a statistical distribution.

F-test

A statistical test used to compare the variances between two populations to determine if they are significantly different.

p-value

The probability level which forms the basis for deciding if a null hypothesis should be rejected.

Type I Error

The incorrect rejection of a true null hypothesis, also known as a false positive.

Type II Error

The failure to reject a false null hypothesis, also known as a false negative.

Standardized Variable

A variable that has been rescaled to have a mean of zero and a standard deviation of one.

Confidence Interval

A range of values derived from sample statistics that is likely to contain the true value of an unknown population parameter.

Statistical Significance

A determination that the relationship observed in the sample data is unlikely to have occurred by chance alone.

Endogenous Variable

A variable whose value is determined by the relationship within the model.

Exogenous Variable

A variable that is not affected by other variables in the model and is considered to be operationally independent.

Auxiliary Equation

An additional equation used to help understand the relationships between variables in regression analysis.

Attenuation Bias

The bias that occurs when measurements of an independent variable are in error, usually resulting in underestimating the effect of that variable.

Goodness of Fit

A measure of how well a statistical model fits the data it is intended to model.

Homoskedasticity

A condition in regression analysis where the variance of the errors is constant across all levels of independent variables.

Heteroskedasticity

A situation in regression analysis where the variance of the errors varies across observations.