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  2. MCAT Critical Analysis and Reasoning Skills
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MCAT Critical Analysis and Reasoning Skills Flashcards: Cause Effect Relationships

Study Cause Effect Relationships in MCAT Critical Analysis and Reasoning Skills with focused flashcards that help you recognize the idea, recall the key rule, and apply it in practice-style prompts.

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What this deck covers

This deck focuses on Cause Effect Relationships, giving you a quick way to review the definitions, rules, and examples that matter most for MCAT Critical Analysis and Reasoning Skills.

How to use these flashcards

Work through these flashcards in short sessions. Try to answer each prompt before flipping the card, then revisit any cards you miss until the explanation feels automatic.

MCAT Critical Analysis and Reasoning Skills Flashcards: Cause Effect Relationships

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QUESTION

Which option best describes a bidirectional causal relationship between two variables?

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ANSWER

Each variable influences the other in a feedback loop. Mutual influence creates a cycle where each factor affects and is affected by the other.

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Flashcard 1: Which option best describes a bidirectional causal relationship between two variables?

Answer: Each variable influences the other in a feedback loop. Mutual influence creates a cycle where each factor affects and is affected by the other.

Flashcard 2: What is a necessary cause (necessary condition) in cause-and-effect reasoning?

Answer: A factor that must be present for the effect to occur. Without this factor, the effect cannot happen, establishing it as a prerequisite in causal logic.

Flashcard 3: What is a sufficient cause (sufficient condition) in cause-and-effect reasoning?

Answer: A factor that, if present, guarantees the effect occurs. Its presence alone ensures the effect, distinguishing it from factors that merely contribute.

Flashcard 4: Which option best describes a contributing cause in an argument?

Answer: A factor that increases likelihood or magnitude of an effect. It enhances the probability or intensity of the outcome but is not solely responsible.

Flashcard 5: What is a confounder in a causal claim?

Answer: A third variable causing both the presumed cause and effect. This external factor creates a spurious link by independently influencing both variables.

Flashcard 6: What is reverse causation in an argument that links two variables?

Answer: The alleged effect actually causes the alleged cause. It reverses the assumed direction, where the supposed outcome actually drives the presumed trigger.

Flashcard 7: What is the post hoc ergo propter hoc fallacy in causal reasoning?

Answer: Inferring causation solely because one event follows another. This fallacy assumes temporal sequence implies causality without further evidence.

Flashcard 8: What is the fallacy of confusing necessary and sufficient conditions?

Answer: Treating a necessary condition as sufficient, or vice versa. It errs by equating required conditions with those adequate to produce the result.

Flashcard 9: What is a causal chain in an argument, and what does it imply?

Answer: A causes B causes C; intermediate steps mediate the final effect. This structure shows sequential causation, where initial events trigger subsequent ones leading to the end result.

Flashcard 10: What is a mediator variable in a causal explanation?

Answer: A variable through which the cause produces the effect. It serves as the intermediate mechanism explaining how the cause leads to the effect.

Flashcard 11: What is a moderator variable in a causal claim?

Answer: A variable that changes the strength or direction of an effect. It alters the causal relationship's strength or nature under different conditions.

Flashcard 12: What is the key evidence feature of a causal claim versus a descriptive claim?

Answer: Causal claims require a mechanism or ruling out alternatives. Unlike descriptive claims, causal ones need mechanisms or exclusion of confounders to substantiate the link.

Flashcard 13: What is the difference between correlation and causation in a CARS argument?

Answer: Correlation is association; causation is a producing relationship. Correlation merely shows variables covary, while causation requires evidence that one directly influences the other.