Question
QUESTION 1. Which of the following data mining methods in XLMINER is especially suited for (and limited to) both categorical predictor and outcome variable? a.
QUESTION 1. Which of the following data mining methods in XLMINER is especially suited for (and limited to) both categorical predictor and outcome variable?
a. Nave Bayes method.
b. Regression
c. Neural Network
d. K-Nearest Neighbor method.
QUESTION 2. Which of the following statement(s) is(are) correct?
a. In multiple linear regression, dropping predictors that are uncorrelated with the dependent variable may decrease the variance of predictions.
b. In multiple linear regression, using predictors that are actually uncorrelated with the dependent variable may decrease the variance of predictions.
c. Both a. and b.
d. Neither a. nor b.
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