DA0-001 · Question #165
Which of the following would be the BEST way to identify multicollinear attributes in a data set?
The correct answer is A. Correlation coefficient. Multicollinearity in a dataset refers to the situation where two or more predictor variables are highly correlated, meaning that one can be linearly predicted from the others with a substantial degree of accuracy. In such cases, the correlation coefficient is a key statistical me
Question
Which of the following would be the BEST way to identify multicollinear attributes in a data set?
Options
- ACorrelation coefficient
- BChi-squared test
- CTwo-sample t-test
- DTwo-way ANOVA
How the community answered
(59 responses)- A93% (55)
- B2% (1)
- C2% (1)
- D3% (2)
Explanation
Multicollinearity in a dataset refers to the situation where two or more predictor variables are highly correlated, meaning that one can be linearly predicted from the others with a substantial degree of accuracy. In such cases, the correlation coefficient is a key statistical measure used to identify the presence of multicollinearity. It quantifies the degree to which two variables are linearly related. The Variance Inflation Factor (VIF) is another commonly used metric that is derived from the correlation coefficient. It assesses how much the variance of an estimated regression coefficient increases if your predictors are correlated. If no factors are correlated, the VIFs will all be equal to 1.
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