The tendency to test hypotheses exclusively through direct testing, in contrast to tests of possible alternative hypotheses:

The tendency to test hypotheses exclusively through direct testing, in contrast to tests of possible alternative hypotheses:

• A. Ambiguity effect
• B. Congruence bias
• C. Illusion of validity
• D. Misconception of chance

Answer: (B)

Congruence bias is the tendency to test a favored hypothesis mainly through direct testing while neglecting tests of alternative explanations. This means you’re aiming to confirm your idea rather than actively seeking disconfirming evidence or considering other plausible hypotheses that could explain the data. The consequence is a biased assessment of reality because the testing approach itself is oriented toward supportive results instead of rigorous falsification. Think about how you’d evaluate a new training method. If you only run experiments that look for improvements and you don’t design tests that could show the method fails, or you don’t compare it to other possible explanations (like placebo effects, natural improvement, or external factors), you’re engaging in congruence bias. To counter it, design studies that can falsify the hypothesis and that explicitly test competing explanations. The other choices aren’t about this testing stance: the ambiguity effect deals with risk preference under uncertainty, the illusion of validity is overconfidence in judgments despite limited data, and the misconception of chance relates to misreading randomness. None of these describe the specific tendency to validate a hypothesis by direct testing while ignoring alternative possibilities.

Congruence bias is the tendency to test a favored hypothesis mainly through direct testing while neglecting tests of alternative explanations. This means you’re aiming to confirm your idea rather than actively seeking disconfirming evidence or considering other plausible hypotheses that could explain the data. The consequence is a biased assessment of reality because the testing approach itself is oriented toward supportive results instead of rigorous falsification.

Think about how you’d evaluate a new training method. If you only run experiments that look for improvements and you don’t design tests that could show the method fails, or you don’t compare it to other possible explanations (like placebo effects, natural improvement, or external factors), you’re engaging in congruence bias. To counter it, design studies that can falsify the hypothesis and that explicitly test competing explanations.

The other choices aren’t about this testing stance: the ambiguity effect deals with risk preference under uncertainty, the illusion of validity is overconfidence in judgments despite limited data, and the misconception of chance relates to misreading randomness. None of these describe the specific tendency to validate a hypothesis by direct testing while ignoring alternative possibilities.