What is true of sample size in relation to decision tree analysis?
A) Ten times the number of predictor variables is the minimum number of observations required for decision tree solutions.
B) Significance testing of decision tree solutions is unreliable with small samples.
C) In larger trees, lower nodes may be based on too few observations, meaning the solution will lack statistical power.
D) Sample size does not matter in decision tree analysis.

Question

Quizplus · Accepted Answer

Answer A is not an accepted standard, though some might use this rule of thumb. Answer B is false because, except for conditional inference trees like "ctree", significance testing is not used in decision tree analysis. Since Answer C is true, Answer D is false.

What Is True of Sample Size in Relation to Decision