Cause and effect in RC
60 flashcards covering Cause and effect in RC for the LSAT Reading Comprehension section.
Cause and effect is a basic logical relationship in reading comprehension, where one event or factor leads to another. For example, in a passage, you might see how a historical event triggered a social change, or how a scientific principle results in a specific outcome. Understanding this helps you grasp the underlying structure of texts, making it easier to follow arguments and draw accurate inferences. It's essential because many passages rely on these relationships to build their main ideas, and misinterpreting them can lead to confusion.
On the LSAT, cause and effect appears in Reading Comprehension questions that ask you to identify causal links, evaluate evidence, or predict outcomes based on passage details. Common traps include mistaking correlation for causation or overlooking subtle language cues, so watch for words like "because," "leads to," or "results in." Focus on how authors use these elements to support claims, as questions often test your ability to differentiate between direct causes and mere associations.
A good tip: Practice mapping out cause-effect chains in practice passages to spot patterns quickly.
Terms (60)
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Cause
In Reading Comprehension, a cause is an event, action, or factor that directly leads to another event or outcome, often indicated by specific language in the passage.
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Effect
An effect is the result or consequence that occurs because of a cause, typically described in passages to show relationships between events or ideas.
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Causal relationship
A causal relationship exists when one event (the cause) directly influences or produces another event (the effect), which passages may explicitly state or imply through evidence.
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Signal words for cause
Signal words for cause, such as 'because', 'since', 'due to', or 'as a result of', help identify where a passage explains why something happens.
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Signal words for effect
Signal words for effect, like 'therefore', 'consequently', 'thus', or 'leads to', indicate the outcome or result of a cause in the text.
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Correlation vs. Causation
Correlation means two events occur together, while causation means one event causes the other; passages often test the error of assuming correlation implies causation.
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Necessary condition
A necessary condition is something that must be true for an effect to occur, but it alone may not be sufficient, as seen in logical arguments within passages.
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Sufficient condition
A sufficient condition is something that, if true, guarantees an effect will occur, which passages might use to build causal chains.
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Reversing cause and effect
Reversing cause and effect is a common error where the actual cause is mistaken for the effect, often appearing in misleading answer choices on the LSAT.
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Post hoc fallacy
The post hoc fallacy assumes that because one event follows another, the first caused the second, which passages may critique or exemplify.
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Common cause fallacy
The common cause fallacy occurs when two events are linked by a third unseen factor, rather than one causing the other, as sometimes implied in RC passages.
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Identifying cause in a passage
Identifying cause in a passage involves looking for language that links an action or event to its outcome, helping to answer questions about relationships.
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Question types on cause and effect
Question types on cause and effect include those asking to strengthen, weaken, or identify causal links, requiring analysis of passage evidence.
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Strengthening a causal argument
Strengthening a causal argument means providing evidence that supports the link between cause and effect, such as additional examples or controlled studies in passages.
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Weakening a causal argument
Weakening a causal argument involves introducing alternative explanations or counterevidence that challenges the proposed cause-effect relationship in the text.
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Counterexamples to causation
Counterexamples to causation are instances where the supposed cause does not produce the effect, used in passages to test the validity of claims.
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Alternative explanations
Alternative explanations are other possible causes for an effect, which passages might present to complicate or refute a primary causal claim.
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Control groups in passages
Control groups in passages refer to elements in experiments described that help isolate the cause by comparing outcomes with and without the variable.
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Longitudinal studies and causation
Longitudinal studies and causation involve tracking events over time in passages to establish whether one factor reliably leads to another.
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Cross-sectional studies limitations
Cross-sectional studies limitations include their inability to prove causation due to examining data at a single point, as noted in some RC passages.
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Author’s use of causal language
The author’s use of causal language shapes how readers interpret relationships, often employing it to build arguments or explain phenomena.
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Implicit vs. Explicit causation
Implicit causation is suggested indirectly through evidence, while explicit causation is stated outright, both appearing in passages for analysis.
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Cause and effect in historical passages
In historical passages, cause and effect explain events like wars or revolutions, linking preceding factors to outcomes.
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Cause and effect in scientific passages
In scientific passages, cause and effect describe hypotheses, experiments, and results, showing how variables influence one another.
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Cause and effect in social science passages
In social science passages, cause and effect explore human behavior, linking societal factors to outcomes like economic changes.
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Diagrams representing cause and effect
Diagrams in passages, such as flowcharts, visually represent cause and effect to clarify complex relationships between elements.
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Flowcharts in RC
Flowcharts in RC passages illustrate sequences of cause and effect, helping to visualize how one event triggers another.
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Predicting effects from causes
Predicting effects from causes involves using passage information to forecast outcomes based on established causal links.
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Inferring causes from effects
Inferring causes from effects means deducing the likely origin of an outcome based on clues provided in the passage.
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Evaluating evidence for causation
Evaluating evidence for causation requires assessing the strength of passage data, such as whether it rules out coincidences.
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Role of evidence in causal claims
The role of evidence in causal claims is to support or refute links, with passages often providing data to back up or challenge assertions.
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Biases in causal reasoning
Biases in causal reasoning, like overlooking alternatives, can skew interpretations in passages and must be identified in questions.
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Confirmation bias in RC
Confirmation bias in RC is the tendency to favor evidence that supports a causal claim, which passages might illustrate as a flaw.
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Availability heuristic
The availability heuristic affects causal reasoning by relying on readily recalled examples, potentially leading to errors in passage analysis.
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Overgeneralization
Overgeneralization in causal arguments extends a single cause-effect instance to all cases, a trap often present in RC passages.
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Straw man in causal arguments
A straw man in causal arguments misrepresents an opposing view to make the author's cause seem stronger, appearing in debated passages.
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Slippery slope
A slippery slope argument claims one cause will lead to a chain of extreme effects, which passages may use or criticize.
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Begging the question in causation
Begging the question in causation assumes the cause is true without proof, a circular reasoning flaw in some passage arguments.
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Analogies in causal explanations
Analogies in causal explanations compare situations to illustrate how one cause leads to an effect, aiding comprehension in passages.
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Hypotheticals testing causation
Hypotheticals testing causation pose 'what if' scenarios in passages to examine whether a proposed cause truly produces an effect.
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Strategy for cause and effect questions
A strategy for cause and effect questions is to map out the passage's relationships and check answer choices against the evidence.
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Eliminating answer choices based on causation
Eliminating answer choices based on causation involves rejecting options that misrepresent or ignore the passage's causal links.
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Main point questions involving cause and effect
Main point questions involving cause and effect require identifying how causal relationships contribute to the passage's overall argument.
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Detail questions on causal elements
Detail questions on causal elements ask for specific evidence from the passage that supports or defines a cause-effect link.
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Inference questions about unseen causes
Inference questions about unseen causes prompt deducing hidden factors based on the effects described in the passage.
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Application of cause and effect to new scenarios
Application of cause and effect to new scenarios means using passage principles to predict outcomes in hypothetical situations.
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Common wrong answer types for causal questions
Common wrong answer types for causal questions include those that reverse cause and effect or introduce irrelevant correlations.
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Misinterpreting temporal sequence
Misinterpreting temporal sequence is confusing the order of events as proof of causation, a pitfall in timing-related passage details.
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Confusing correlation with causation in passages
Confusing correlation with causation in passages leads to incorrect inferences, as tested in questions about statistical relationships.
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Identifying multiple causes
Identifying multiple causes involves recognizing that an effect may result from several factors, as complex passages often demonstrate.
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Chain of causation
A chain of causation is a series of linked causes and effects, like a domino effect, depicted in some RC narratives.
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Intervening variables
Intervening variables are factors that influence the relationship between cause and effect, potentially altering outcomes in passages.
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Direct vs. Indirect causes
Direct causes immediately produce an effect, while indirect causes do so through intermediate steps, both relevant in passage analysis.
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Positive and negative effects
Positive effects are beneficial outcomes of a cause, and negative effects are harmful ones, as passages might contrast them.
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Threshold effects
Threshold effects occur when a cause only produces an effect after reaching a certain level, a concept in scientific RC passages.
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Dose-response relationships
Dose-response relationships show how the strength of a cause affects the magnitude of an effect, often in health-related passages.
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Feedback loops
Feedback loops are cycles where an effect influences the original cause, creating ongoing processes in some passages.
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Causal mechanisms
Causal mechanisms are the processes explaining how a cause leads to an effect, detailed in explanatory passages.
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Experimental vs. Observational evidence
Experimental evidence tests causation through controlled trials, while observational evidence infers it from patterns, as discussed in RC.
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Falsifiability of causal claims
Falsifiability of causal claims means they can be proven wrong with evidence, a principle for evaluating arguments in passages.