When considering the decisions errors that can be made in hypothesis testing, one must balance the dangers of Type I versus Type II errors. Usually statistical testing is biased toward avoiding _____errors.
A) mathematical or computational
B) Type I
C) Type II
D) decisional

Question

Quizplus · Accepted Answer

Type I errors (false positives) are generally considered more serious and are thus more strongly avoided in hypothesis testing. This is because a Type I error means incorrectly rejecting the null hypothesis, potentially leading to the assumption that an effect or difference exists when it does not.

When Considering the Decisions Errors That Can Be Made in Hypothesis