Set Type
Adjusted R2
Goodness-of-fit measure that adjusts the coefficient of determination, R2,
for the number of independent variables in the model.
Akaike's information criterion (AIC)
A statistic used to compare sets of independent variables for explaining a
dependent variable. It is preferred for finding the model that is best suited
for prediction.
Analysis of variance (ANOVA)
The analysis that breaks the total variability of a dataset (such as
observations on the dependent variable in a regression) into components
representing different sources of variation.
Breusch–Godfrey (BG) test
A test used to detect autocorrelated residuals up to a predesignated order
of the lagged residuals.
Breusch–Pagan (BP) test
A test for the presence of heteroskedasticity in a regression.
Coefficient of determination
The percentage of the variation of the dependent variable that is
explained by the independent variables. Also referred to as the R-squared
or R2.
Conditional heteroskedasticity
A condition in which the variance of residuals of a regression are
correlated with the value of the independent variables.
Cook's distance
A metric for identifying influential data points. Also known as Cook's D
(Di).
Dummy variable
An independent variable that takes on a value of either 1 or 0, depending
on a specified condition. Also known as an indicator variable.
Durbin–Watson (DW) test
A test for the presence of first-order serial correlation.
First-order serial correlation
, The correlation of residuals with residuals adjacent in time.
General linear F-test
A test statistic used to assess the goodness of fit for an entire regression
model, so it tests all independent variables in the model.
Heteroskedastic
When the variance of the residuals differs across observations in a
regression.
High-leverage point
An observation of an independent variable that has an extreme value and
is potentially influential.
Influence plot
A visual that shows, for all observations, studentized residuals on the y-
axis, leverage on the x-axis, and Cook's D as circles whose size is
proportional to the degree of influence of the given observation.
Influential observation
An observation in a statistical analysis whose inclusion may significantly
alter regression results.
Interaction term
A term that combines two or more variables and represents their joint
influence on the dependent variable.
Intercept dummy
An indicator variable that allows a single regression model to estimate two
lines of best fit, each with differing intercepts, depending on whether the
dummy takes a value of 1 or 0.
Joint test of hypotheses
The test of hypotheses that specify values for two or more independent
variables in the hypotheses.
Leverage
A measure for identifying a potentially influential high-leverage point.
Likelihood ratio (LR) test
A method to assess the fit of logistic regression models and is based on
the log-likelihood metric that describes the model's fit to the data.
Log odds
Adjusted R2
Goodness-of-fit measure that adjusts the coefficient of determination, R2,
for the number of independent variables in the model.
Akaike's information criterion (AIC)
A statistic used to compare sets of independent variables for explaining a
dependent variable. It is preferred for finding the model that is best suited
for prediction.
Analysis of variance (ANOVA)
The analysis that breaks the total variability of a dataset (such as
observations on the dependent variable in a regression) into components
representing different sources of variation.
Breusch–Godfrey (BG) test
A test used to detect autocorrelated residuals up to a predesignated order
of the lagged residuals.
Breusch–Pagan (BP) test
A test for the presence of heteroskedasticity in a regression.
Coefficient of determination
The percentage of the variation of the dependent variable that is
explained by the independent variables. Also referred to as the R-squared
or R2.
Conditional heteroskedasticity
A condition in which the variance of residuals of a regression are
correlated with the value of the independent variables.
Cook's distance
A metric for identifying influential data points. Also known as Cook's D
(Di).
Dummy variable
An independent variable that takes on a value of either 1 or 0, depending
on a specified condition. Also known as an indicator variable.
Durbin–Watson (DW) test
A test for the presence of first-order serial correlation.
First-order serial correlation
, The correlation of residuals with residuals adjacent in time.
General linear F-test
A test statistic used to assess the goodness of fit for an entire regression
model, so it tests all independent variables in the model.
Heteroskedastic
When the variance of the residuals differs across observations in a
regression.
High-leverage point
An observation of an independent variable that has an extreme value and
is potentially influential.
Influence plot
A visual that shows, for all observations, studentized residuals on the y-
axis, leverage on the x-axis, and Cook's D as circles whose size is
proportional to the degree of influence of the given observation.
Influential observation
An observation in a statistical analysis whose inclusion may significantly
alter regression results.
Interaction term
A term that combines two or more variables and represents their joint
influence on the dependent variable.
Intercept dummy
An indicator variable that allows a single regression model to estimate two
lines of best fit, each with differing intercepts, depending on whether the
dummy takes a value of 1 or 0.
Joint test of hypotheses
The test of hypotheses that specify values for two or more independent
variables in the hypotheses.
Leverage
A measure for identifying a potentially influential high-leverage point.
Likelihood ratio (LR) test
A method to assess the fit of logistic regression models and is based on
the log-likelihood metric that describes the model's fit to the data.
Log odds
