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Term: Multicollinearity

Definition:

Multicollinearity refers to the high correlation between independent variables in a regression analysis, which can lead to issues such as unreliable and misleading coefficient estimates.

Senses:

• Sense 1: (Statistics) The state or condition of having a strong correlation between two or more independent variables.

Usages:

1. Usage 1: Multicollinearity is a common problem in regression analysis that can affect the accuracy and interpretation of results.
2. Usage 2: Researchers should assess and address multicollinearity to ensure the reliability of their findings.
3. Usage 3: High multicollinearity among predictors may require additional data or feature selection techniques to improve the model.

Sample Sentences:

1. To detect multicollinearity, analysts often calculate the variance inflation factor.

2. The presence of multicollinearity in the dataset made it challenging to identify the true effect of each independent variable.

3. The researcher conducted a multicollinearity test to assess the relationship between the predictors.

Related Products:

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