Multiple Regression Analysis: Inference

This set of flashcards covers key vocabulary and concepts related to multiple regression analysis and hypothesis testing.

Multiple Regression Analysis

A statistical technique that models the relationship between a dependent variable and multiple independent variables.

t-test

A statistical test used to compare the means of two groups or to test the significance of a single parameter.

F-test

A statistical test used to compare the variances between two or more groups to assess if at least one group mean is different.

Null Hypothesis (H0)

The default assumption that there is no effect or no difference, which is tested against an alternative hypothesis.

Alternative Hypothesis (H1)

The hypothesis that there is an effect or a difference; it is accepted if the null hypothesis is rejected.

Sum of Squared Residuals (SSR)

A measure of the variation in the dependent variable that is unexplained by the independent variables in the regression model.

R-squared (R2)

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

Significance Level

The probability of rejecting the null hypothesis when it is true; commonly set at 0.05.

Degrees of Freedom (df)

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

Reparameterization

The process of defining new parameters for a model, which can simplify the interpretation and testing of hypotheses.

Joint Hypothesis Test

A statistical test that assesses more than one hypothesis at the same time.

Critical Value

A point on the test distribution that is compared to the test statistic to decide whether to reject the null hypothesis.

Covariance

A measure of how much two random variables vary together.

Exclusion Restriction

A restriction that states that a particular parameter in the model is equal to zero.

p-value

The probability of obtaining a test statistic at least as extreme as the one observed, assuming the null hypothesis is true.

Statistically Significant

A result is considered statistically significant if it is unlikely to have occurred under the null hypothesis.

One-sided test

A statistical test that evaluates the possibility of an effect in one direction.

Two-sided test

A statistical test that evaluates the possibility of an effect in both directions.

Variance

A statistical measurement that describes the dispersion of data points in a data series.

Dependent Variable

The variable in a statistical model that is being predicted or explained.

Independent Variable

The variable in a statistical model that provides input or is manipulated to observe its effect on the dependent variable.