STATISTICAL TECHNIQUES AND TOOLS
MULTIPLE REGRESSION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Variable Selection Methods are helpful when
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the researcher is not basing predictors on theory
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has many variables (10 or more) under consideration
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wants to easily disregard IVs that cause multicollinearity
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All of the above
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Explanation:
Detailed explanation-1: -Classical variable selection methods include forward selection, backward elimination, and stepwise selection. The names are tied with the direction of the significant variable search.
Detailed explanation-2: -The variables for the model were selected using the stepwise selection method, the most common method for variable selection that permits using both forward and backward procedures iteratively in model building.
Detailed explanation-3: -Chi-square Test. Fisher’s Score. Correlation Coefficient. Dispersion Ratio. Backward Feature Elimination. Recursive Feature Elimination. Random Forest Importance. 10-Oct-2020
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