Test statistic that quantifies the amount of variability in a dependent variable explained by the regression model's independent variable(s).
The Coefficient of Determination, denoted as R^2, measures the proportion of the variance in the dependent variable that is predictable from the independent variable(s). It is commonly used in the context of regression analysis to determine how well the model fits the data.
A statistical measure of the degree to which the movements of two variables are related. It quantifies the direction and strength of the relationship between variables.
In the field of statistics, a dependent variable is the subject of an equation whose value depends on independent variables. Typically denoted as 'Y', the dependent variable is influenced or predicted by the independent variables, often denoted as 'X'.
Two or more variables that are in no way associated with or dependent on each other.
Multicollinearity refers to the presence of independent variables in regression analysis that are associated with each other, having some degree of correlation. This phenomenon can complicate the interpretation of model coefficients and lead to unreliable results.
Multiple regression is a statistical method used to examine the relationship between one dependent variable and two or more independent variables. This technique helps in understanding how multiple factors simultaneously affect the dependent variable.
Regression analysis is a statistical technique used to establish the relationship between a dependent variable and one or more independent variables. It is widely used in various fields to predict future values and measure the significance of different factors.
A regression line is a line calculated in regression analysis that is used to estimate the relationship between two quantities, the independent variable and the dependent variable.
A problem that arises in regression analysis involving time series data when successive values of the random error term are not independent. This implies that an important variable has not been identified. Same as autocorrelation.
Simple Linear Regression: Method for Analyzing the Relationship Between One Independent Variable and One Dependent Variable
A stochastic process or variable relies on probabilistic behavior and chance, commonly used in fields like statistics, finance, and engineering to model systems that are inherently random.
