Are mutually exclusive or incoherent events independent or dependent?
If events are incoherent, they must not be independent, that is, they must be dependent events. Why is that? Remember: if A and B are disjoint, they cannot happen together. In other words, if A and B are incoherent events, it means that if event A occurs, B does not occur and vice versa.
What happens when independent variables are correlated?
When independent variables are highly correlated, change in one variable would cause change in another and thus the model results fluctuate significantly. The model results will be unstable and vary a lot with a small change in the data or model.
What happens if the correlation between independent variables is high?
Multicollinearity occurs when independent variables are correlated in a regression model. This correlation is a problem because independent variables must be independent. If the degree of correlation between variables is high enough, it can cause problems in fitting the model and interpreting the results.
How do you recognize multicollinearity?
Multicollinearity can also be detected using tolerance and the mutual variance inflation factor (VIF). If the tolerance value is less than 0.2 or 0.1 and at the same time the value of VIF is 10 and above, then the multicollinearity is problematic.
How do you deal with a high correlation?
Try one of these:
- Remove highly correlated predictors from the model. If you have two or more factors with a high VIF, remove one from the model.
- Use Partial Least Squares Regression (PLS) or Principal Components Analysis, regression methods that reduce the number of predictors to a smaller set of uncorrelated components.
How high is a high correlation?
High degree: If the coefficient value is between ±0.50 and ±1, there is a strong correlation. Moderate degree: If the value is between ±0.30 and ±0.49, there is a mean correlation. Low degree: When the value is below +. 29, then there is a small correlation.
What does it mean to have a weak negative correlation?
A negative correlation is a relationship between two variables moving in opposite directions. In other words, when variable A increases, variable B decreases. A negative correlation is also known as an inverse correlation. As another example, these variables may also have a weak negative correlation.