GMAT Focus Edition flashcards

When sampling without replacement from a large population, the probability of success can be approximated using binomial probability if the sample size is small relative to the population.

• Used when there are two possible outcomes (success/failure).
• Probability of success remains constant for each trial (approximately).
• Trials are independent (approximately).

Memory trick: Probability's a path, count the good, divide by all the math.

A relationship between two quantities where an increase in one leads to a decrease in the other, such that their product remains constant.

• Example: More workers means less time to complete a task.
• Formula: x1*y1 = x2*y2
• Often seen in 'work rate' problems.

Memory trick: Proportions link numbers, direct or inverse, they show how things stir.

The sum of a set of numbers divided by the count of the numbers in the set. Also known as average.

• Formula: Sum / Count = Mean.
• Used to find the central tendency of data.
• Can be used to find a missing value if the mean and other values are known.

Memory trick: Average is sum over count, a balance found.

For a round trip with different speeds, the average speed is calculated as total distance divided by total time, which is equivalent to the harmonic mean of the two speeds.

• Not the simple arithmetic average of speeds.
• Harmonic mean formula: 2 / (1/v1 + 1/v2).
• Requires considering time spent at each speed.

Memory trick: Distance over time, that's speed's true rhyme; average speed, total path, total time.

Problems involving combining two or more quantities with different concentrations to form a mixture with a desired concentration.

• Often solved using a system of linear equations.
• One equation for total volume/quantity, another for total amount of substance.
• Concentration is substance amount / total volume.

Memory trick: Words to equations, variables in play, solve with logic, come what may.

When a quadratic equation is given in Data Sufficiency, it often yields two possible values for the variable, requiring additional information to determine a unique solution.

• Factoring or quadratic formula gives solutions.
• Two distinct real roots are common.
• Additional statements must narrow down to a single root.

Memory trick: Unique means one, no more, no less; else, it fails the sufficiency test.

To challenge an argument based on analogy, one must demonstrate a critical difference between the two situations being compared that makes the analogy inappropriate or misleading.

• Focus on dissimilarity between the compared items.
• The difference must be relevant to the conclusion being drawn.
• A strong challenge shows the analogy's conclusion won't hold.

Memory trick: Analogies are like twins, but if they're not identical, the comparison fails.

Refuting a foundational premise involves demonstrating that a core assumption or a key piece of information upon which an argument is built is incorrect or insufficient to support the conclusion.

• Targets the core 'if-then' logic of an argument.
• Shows that the stated means will not achieve the stated end.
• Often identifies a critical omission or mischaracterization of the problem.

Memory trick: If the foundation is cracked, the building won't stand.

To weaken a causal claim by identifying a confounding variable means introducing a third factor that is related to both the presumed cause and effect, thereby offering an alternative explanation for the observed correlation.

• Introduces a third variable (Z).
• Z is related to both X (cause) and Y (effect).
• Z potentially explains the correlation between X and Y.

Memory trick: Is it A causes B, or B causes A, or C causes both?

Introducing new information that makes a counter-argument more convincing or highlights additional drawbacks of a proposed plan, thereby reinforcing its rejection.

• Adds weight to the 'against' side of a debate.
• Can reveal hidden costs, negative impacts, or impracticalities.
• Often provides a stronger justification for an alternative course of action or inaction.

Memory trick: Find the extra weight for *your* side of the scale.

To challenge the effectiveness of a proposed cause, show that the observed correlation is not causal, or that other factors are the true drivers of the desired outcome.

• Correlation does not imply causation.
• Identify confounding variables.
• Look for temporal precedence issues.

Memory trick: Don't just follow the crowd, check if the influencer's shout is truly loud!

A situation where a proposed action or change, while having a positive impact in one area, simultaneously produces negative or offsetting impacts in another, undermining the overall claimed benefit.

• Highlights trade-offs or unintended consequences.
• Shows that a single-focus improvement might not lead to a net positive.
• Requires considering the full scope of an action's impact.

Memory trick: Every silver lining can have a cloudy edge.

To strengthen a claim that A causes B, provide evidence that removes alternative explanations, confirms the mechanism, or shows a direct link.

• Rule out confounding variables.
• Establish a plausible mechanism.
• Demonstrate consistency across different contexts.

Memory trick: Build up the bridge, remove the fog, confirm the plot, and the argument is solid rock!

To strengthen an argument means to provide additional evidence or reasoning that makes the conclusion more likely to be true, often by ruling out alternative explanations or confirming a causal link.

• Eliminates alternative causes.
• Provides additional supporting evidence.
• Confirms the stated causal relationship.

Memory trick: Strong arguments eliminate rivals and confirm connections.

To challenge a foundational assumption is to attack the underlying, often unstated, belief that an argument relies upon for its validity. If the assumption is false, the argument collapses.

• Targets the implicit beliefs of an argument.
• If proven false, the argument's conclusion is significantly weakened.
• Often involves questioning causality or generalizability.

Memory trick: Find the hidden pillar, then knock it down.

To support a contention means to provide factual evidence or logical reasoning that directly reinforces the truth or likelihood of a particular claim or argument being made, often by demonstrating its underlying mechanism or consequence.

• Provides direct evidence for the claim.
• Explains the mechanism of the claim.
• Shows logical consequence of the claim.

Memory trick: Claims gain strength from direct evidence and clear consequences.

Undermining an argument by showing that the proposed solution addresses a secondary or incorrect cause of the problem, rather than the primary or true cause.

• Shifts focus from the proposed solution's efficacy to the problem's root cause.
• Implies the solution will be ineffective because it targets the wrong issue.
• Often involves identifying a more fundamental or pervasive cause.

Memory trick: Is this the right key for *this* lock, or just *a* lock?

Using data or findings from one context to draw conclusions or make recommendations in a different context where the underlying conditions or populations may not be comparable.

• Involves an invalid transfer of conclusions.
• Often arises from overlooking demographic or contextual differences.
• Weakens arguments that rely on the direct applicability of external studies.

Memory trick: Is the advice 'fit for purpose' for THIS specific situation?

To weaken a causal claim, identify other plausible factors that could explain the observed effect, besides the one proposed.

• Correlation is not causation.
• Look for confounding variables.
• Consider external influences.

Memory trick: Don't assume 'because of' without checking all the 'why's and 'what for's!

When evaluating claims, especially in areas like health or product efficacy, it's crucial to consider all relevant data, including potential negative impacts, long-term effects, and the scope of applicability, to ensure accuracy and avoid misleading consumers.

• Safety data is paramount for health claims.
• Long-term effects can alter efficacy perception.
• Scope of efficacy (who it works for) is vital.

Memory trick: Valid claims weigh benefits against risks, scope, and duration.

To effectively challenge a claim about a solution's impact, identify a significant factor or cause that the proposed solution does not address, or that outweighs the addressed factor.

• Focus on the 'overall' or 'significant' impact claims.
• Look for unmentioned, major contributors to the problem.
• The overlooked factor must be substantial enough to negate or diminish the claimed effect.

Memory trick: Don't just fix the leaky faucet if the whole pipe is burst!

To doubt a claim of primary causation, look for evidence of alternative causes, or evidence that the claimed cause was not present when the effect began.

• Correlation does not equal causation.
• Temporal precedence is key for causation.
• Multiple factors often contribute to complex phenomena.

Memory trick: When a conclusion's too neat, check if its timeline's complete!

The extent to which the results of a study or experiment can be applied to a broader population or different settings.

• Depends on representativeness of sample.
• Contextual factors can limit generalizability.
• Voluntary participation can introduce self-selection bias.

Memory trick: Don't accept claims without checking their roots, especially if the sample has fruits!

To weaken a proposed causal mechanism, one can introduce an alternative cause for the observed effect, demonstrate reverse causation, or show that the mechanism is implausible.

• Introduces a different reason for the outcome.
• Challenges the direction of the cause-effect link.
• Focuses on undermining 'how' or 'why' the effect occurs.

Memory trick: Is it A causes B, or B causes A, or C causes both?

To strengthen a specific link between a cause and an effect, one must provide evidence that clarifies or reinforces the mechanism by which that particular cause leads to that particular effect.

• Explains the 'how' or 'why' of a causal relationship.
• Focuses on the specific interaction between cause and effect.
• Can involve detailing a process or condition that enables the link.

Memory trick: Show the bridge, don't just say it's there.

To re-evaluate a claim of 'unreliable', consider if the definition of reliability or the user's actual needs are being misapplied or misunderstood.

• Reliability is context-dependent.
• Different users have different needs.
• Functionality beyond the criticized aspect can be important.

Memory trick: To make a conclusion falter, find its hidden assumption, or its context alter!

Presenting a different, plausible explanation for an observed phenomenon that competes with the proposed cause, thereby weakening the original causal claim.

• Introduces a confounding variable.
• Challenges the uniqueness of the proposed cause.
• Often involves a concurrent event or pre-existing condition.

Memory trick: Just because A happened before B, doesn't mean A caused B.

Identifying a primary unaddressed cause involves pointing out a major source of a problem or impact that a proposed solution fails to tackle, thereby questioning the solution's effectiveness in achieving its stated broad goals.

• Solution focuses on a secondary problem source.
• A larger, primary source is ignored.
• Challenges the 'significance' of the solution's impact.

Memory trick: Don't just fix the ant hill if there's a mountain to move.

An assumption in an argument is an unstated premise that must be true for the conclusion to logically follow from the stated premises. It bridges the gap between the evidence and the conclusion.

• It's unstated.
• It's necessary for the conclusion.
• If false, the conclusion is weakened or invalid.

Memory trick: Assumptions are the unstated bridges that hold the argument together.

To challenge a claim that an inaccuracy or flaw is 'negligible,' one must demonstrate that the supposed negligible factor has a significant practical impact on the intended use, outcome, or user experience, thereby proving its importance.

• Demonstrate practical significance.
• Connect inaccuracy to user goals.
• Show negative impact on desired outcomes.

Memory trick: Negligible claims crumble when practical impact is shown to be significant.

The practical importance of a treatment effect, indicating whether the observed change is meaningful for a patient's health or quality of life, beyond just statistical significance.

• Distinguished from statistical significance.
• Focuses on real-world impact.
• Often determined by expert consensus or patient-reported outcomes.

Memory trick: When a drug is 'effective' claimed, check if the patient's life is truly tamed!

An explanation for an observed effect that is different from the one proposed, thereby weakening the original causal claim.

• Provides a competing reason for an outcome.
• Directly challenges the assumed cause-and-effect relationship.
• Often involves identifying a confounding variable.

Memory trick: Always look for the 'other guy' who might be responsible.

The logical fallacy of assuming that because two events or variables are correlated (occur together or in sequence), one must necessarily be the cause of the other, without considering confounding variables or alternative explanations.

• Correlation indicates a relationship, not cause.
• Confounding variables can create spurious correlations.
• Proper experiments are needed to establish causation.

Memory trick: Correlation's a link, but causation needs more than just a blink.

To weaken advice based on a generalization, show that the specific case differs significantly from the general group in a way that impacts the effectiveness of the advice.

• Identify the generalization being made (e.g., 'effective for X type of brands').
• Identify the specific case (e.g., 'this startup's product').
• Find a crucial difference between the general and specific that invalidates the generalization's applicability.

Memory trick: A map for cars won't help a boat.

A type of bias where individuals select themselves into a group, causing the group to have pre-existing characteristics that influence the outcome, rather than the intervention itself.

• Occurs when participants are not randomly assigned.
• Can lead to misleading conclusions about cause-and-effect.
• Look for pre-existing differences in groups being compared.

Memory trick: Did the magic potion work, or were they already healthy?

To doubt a projection based on a 'primary driver', identify evidence that suggests a different factor is the actual primary driver or that the assumed driver is not as important as believed.

• Focus on the stated 'primary' or 'most important' factor.
• Look for evidence that contradicts this prioritization.
• The alternative factor must be substantial enough to invalidate the projection.

Memory trick: Building a house on sand: the foundation isn't solid.

To strengthen a causal claim, provide additional evidence that supports the proposed mechanism by which the cause leads to the effect, or rule out alternative causes.

• Focus on the 'how' and 'why' of the relationship.
• Look for evidence that confirms intermediate steps or associated conditions.
• Eliminating alternative explanations also strengthens the original claim.

Memory trick: Adding a missing piece to the puzzle makes the picture clearer.

To weaken a specific reason given for an observed effect, introduce an alternative explanation for the effect that is more plausible or equally plausible.

• Focus on the 'why' or 'how' aspect of the claim.
• Look for confounding variables or reverse causation.
• The alternative explanation must directly compete with the proposed reason.

Memory trick: The magician's trick: it wasn't the wand, it was the hidden string!

An alternative explanation for an observed effect proposes a different cause or mechanism than the one originally suggested, often challenging the directness or nature of the initial causal claim.

• Offers a new reason for the observed outcome.
• Challenges the 'how' or 'why' of the effect.
• Can involve physiological, psychological, or environmental factors.

Memory trick: The machine has another gear, not just the one you see.

To challenge a claim of an 'inevitable' negative outcome, provide evidence that mitigates the risk, demonstrates alternative possibilities, or shows the underlying premise is flawed.

• Examine the mechanism of harm.
• Look for mitigating factors.
• Question the scope of the impact.

Memory trick: When a future is 'certain', check the 'how' and 'what if', or the curtain won't close on the predicted rift!

To challenge a claim about securing regulatory approval, identify fundamental flaws in the data collection, trial design, or safety profile that would prevent regulators from deeming the product safe and effective.

• Regulatory approval relies on rigorous scientific evidence.
• Look for issues related to trial design (e.g., control groups, sample size, blinding).
• Safety concerns (serious side effects) are also critical factors.

Memory trick: The bridge needs solid foundations, not just paint.

To cast doubt on a specific causal claim, identify another plausible cause for the observed effect that is also present or part of the scenario.

• Focus on the *specific reason* given for an effect.
• Look for other factors that could produce the same effect.
• The alternative explanation should be a known or likely cause.

Memory trick: Is it the sun, or the lamp making the room bright?

An unstated belief or premise that must be true for an argument's conclusion to logically follow from its stated premises.

• Often links premise to conclusion.
• If false, the argument crumbles.
• Implicit, not explicitly stated.

Memory trick: An assumption is the hidden bridge, if it falls, the argument's on a ledge!

Providing additional evidence that directly supports a cause-and-effect relationship, often by ruling out alternative causes or showing a plausible mechanism.

• Directly links cause to effect.
• Reduces the likelihood of confounding factors.
• Can involve showing a mechanism or independent corroboration.

Memory trick: Connect the dots, prove the mechanism, control the variables.

An unmeasured variable that influences both the supposed cause and the supposed effect, creating a spurious correlation between them.

• Distorts the true relationship between variables.
• Can lead to incorrect causal conclusions.
• Must be controlled for in experimental design.

Memory trick: Just because two trains run on parallel tracks, doesn't mean one pushes the other.

To challenge temporal precedence is to show that the presumed effect occurred before the presumed cause, thereby undermining the possibility of a direct causal relationship.

• Cause must precede effect for causation.
• Evidence showing effect before cause disproves the link.
• Crucial for establishing causality.

Memory trick: The cart can't pull the horse, time must flow forward.

Evaluating the overall effect of a policy or action by considering both positive and negative consequences across all relevant sectors or groups.

• Goes beyond just positive outcomes.
• Requires consideration of trade-offs and opportunity costs.
• Aims for a comprehensive understanding of effects.

Memory trick: Look at ALL the numbers, not just the shiny ones.

An extraneous variable that correlates with both the dependent and independent variables, potentially leading to a spurious correlation or misleading causal inference.

• Can create false causal links.
• Must be controlled for in studies.
• Often related to lifestyle or environment.

Memory trick: When a cause is claimed, seek out the hidden hand, or the link will be unchained!

To undermine an argument that relies on an analogy, one must show that the two situations being compared are significantly different in ways that affect the conclusion, or that the analogy is incomplete or misleading.

• Differences between cases weaken analogy.
• New factors not present in the analogy are important.
• Analogies don't guarantee identical outcomes.

Memory trick: Analogies fail if the core conditions differ or new elements change the outcome.

To evaluate a generalization based on anecdotal evidence (specific examples), one must determine if the examples are truly representative of the larger group or if they are outliers, and consider the prevalence of the observed phenomenon within the entire category.

• Anecdotes may not be representative.
• Look for prevalence across the entire group.
• Beware of selection bias in examples.

Memory trick: Generalizations need broad data, not just a few shining examples.

Drawing a broad conclusion or making a general claim based on a small number of specific, often unrepresentative, personal stories or examples.

• Anecdotes lack statistical power and representativeness.
• Often highlights extreme cases rather than typical outcomes.
• Can lead to misleading conclusions about general trends.

Memory trick: Don't judge the whole book by a few flashy pages.

To reconsider a conclusion means to find new information or an alternative interpretation of existing facts that suggests the original conclusion might be flawed, incomplete, or based on an incorrect premise.

• Introduces a confounding variable.
• Reveals a hidden effect.
• Suggests a different causality.

Memory trick: Revisit conclusions when new info shifts perspective or uncovers hidden effects.

Statistical significance indicates a result is unlikely due to chance; clinical significance indicates a result has practical, real-world importance for patients or practitioners.

• Statistical significance focuses on probability (p-value).
• Clinical significance focuses on practical impact or magnitude of effect.
• A statistically significant finding may not always be clinically significant, and vice versa.

Memory trick: Does the pill work in the lab AND in real life?

To weaken an argument means to introduce information that makes the conclusion less likely to be true, often by providing an alternative explanation for the observed facts or attacking an underlying assumption.

• Introduces alternative causes.
• Challenges the validity of evidence.
• Attacks underlying assumptions.

Memory trick: Weak arguments crumble with alternative causes or flawed foundations.

To weaken a causal claim, identify another plausible factor that could be responsible for the observed effect, thus casting doubt on the proposed cause.

• Focus on the 'cause' and 'effect' identified in the argument.
• Look for external or unconsidered factors.
• The alternative cause must be capable of producing the observed effect.

Memory trick: It wasn't the lucky charm, it was the extra practice!

To refute a claim of a 'net negative outcome,' one must demonstrate that the proposed action, despite its costs, ultimately yields greater benefits or avoids larger detriments, leading to an overall positive or neutral result.

• Focus on the 'net' effect.
• Compare total costs to total benefits over time.
• Consider avoided costs as benefits.

Memory trick: Concerns are unwarranted when benefits outweigh costs, or negative impacts are offset.

Evaluating financial feasibility involves comparing the total costs (initial, operational, maintenance) of a project against its anticipated benefits (revenue, savings) over a defined period, often with a focus on specific points of contention.

• Requires accurate cost and benefit data.
• Must address all significant cost components.
• Considers long-term implications.

Memory trick: Feasibility balances all costs and benefits, especially disputed ones.

To support a financial projection, provide evidence that validates the underlying assumptions about costs, revenues, or efficiency.

• Look for industry benchmarks.
• Evidence of unforeseen savings.
• Confirmation of revenue increases.

Memory trick: To make a claim stand tall, find a strong pillar, or watch it fall!

To rule out a specific cause for an observed effect, provide evidence that the effect occurs independently of the proposed cause or is attributable to a broader, alternative factor.

• Look for confounding variables.
• Compare with control groups/areas.
• Consider broader trends or patterns.

Memory trick: When a direct link is claimed, scan the whole field, or the real cause will remain unnamed!

Exponential growth with a constant doubling time means a quantity consistently doubles over fixed intervals. The formula is N = N₀ * 2^(t/T), where N₀ is initial quantity, t is total time, and T is doubling time.

• Growth is multiplicative, not additive.
• Doubling periods must be calculated first.
• Can be modeled by N = N₀ * 2^n, where n is the number of doubling periods.

Memory trick: Doubling time means hitting 'times two' over and over.