12/06/2022 | By: FDS
Multicollinearity is a statistical phenomenon in which there is variable correlation between multiple variables in a model. It occurs when two or more variables are highly correlated with each other, which can lead to bias in estimates. Multicollinearity can affect the precision of estimates and make it more difficult to determine the individual effects of a variable on the model outcome.
12/06/2022 | By: FDS
Multivariate analysis is a method of statistical analysis that examines multiple variables simultaneously to identify relationships. It is commonly used in the fields of economics, psychology, sociology, and other social sciences to examine complex relationships among multiple variables. Multivariate analysis allows scientists, businesses, and organizations to identify patterns and influences that help them understand and predict behaviors and trends.
12/06/2022 | By: FDS
The Anova test is a statistical procedure used to examine differences between two or more groups. It is often used in research to determine whether mean values differ significantly between two or more groups. The Anova test can also be used as part of a larger design to examine the influence of factors on a particular variable.
12/06/2022 | By: FDS
Resampling is a method for studying the stability of statistics and estimates based on an existing data set. It is used to validate the behavior of estimates by recombining known data to produce new data. This allows the robustness and variance of certain estimates to be determined.
12/06/2022 | By: FDS
A significant relationship is a statistically measurable relationship between two or more variables, the result of which is statistically significant. This means that the relationship between the variables is more than just coincidental and that it really exists. A significant relationship means that a change in one variable is associated with a change in the other variable.