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Inference - Intermediate Level: deductive inference INTERMEDIATE

Comprehensive weakness targeting worksheet covering 20 intermediate-level inference problems. Worksheet 18 of 30 emphasizes deductive inference. Master inductive reasoning, inferential logic, hidden meanings through detailed explanations. Difficulty: moderate complexity with mixed patterns. Tailored for mid-level preparation.

📝 Worksheet 18 of 30 • 20 questions • ⏱️ Estimated time: 20 minutes • 🎯 Intermediate level

What you'll learn in this worksheet:
Your progress through Inference
Worksheet 18 of 30 (60% complete)

Question 1

Statistical information: Only 10% of unprepared students get good grades. Sam is unprepared. What is the most reasonable inference?
This is probabilistic reasoning. The statistical evidence (Only 10% of unprepared students get good grades. Sam is unprepared.) doesn't guarantee certainty, but it provides strong support for: Sam will likely not get good grades

Remember: Probability inferences are about likelihood, not certainty.
probabilistic, statistical, likelihood

Question 2

Rule: If it's raining, there are clouds Observation: There are no clouds What can you logically infer?
This uses the contrapositive rule. The statement "If it's raining, there are clouds" is logically equivalent to its contrapositive: 'If NOT consequence, then NOT condition.' Since we observe "There are no clouds" (the consequence is false), we can conclude "It's not raining" (the condition is false).
contrapositive, modus-tollens

Question 3

Consider this argument: "The team won the championship. They must have the best coach." What unstated assumption must be true for this reasoning to be valid?
The argument makes a hidden assumption: Championship wins indicate best coaching (and the coach was the primary factor in the win)

This assumption is not explicitly stated but is necessary for the conclusion to follow from the premises. If this assumption is false, the argument becomes weak or invalid.
assumption, critical-thinking, argument-analysis

Question 4

Analogical reasoning: "The CEO guides a company like a captain guides a ship." What is the most reasonable inference by analogy?
This uses analogical reasoning: The CEO guides a company like a captain guides a ship.

The analogy maps relationships from the source domain to the target domain, suggesting: The CEO is responsible for the company's direction and safety, just as a captain is for a ship

Analogical inferences are suggestive but not logically certain; the strength depends on the relevance and similarity of the mapped features.
analogy, metaphor, mapping

Question 5

Observation: The light won't turn on. The bulb could be burned out, the switch broken, or there's no power. Which is the most reasonable inference about the cause?
This is abductive reasoning (inference to the best explanation). Given the observation 'The light won't turn on. The bulb could be burned out, the switch broken, or there's no power.', we consider possible causes and select the most plausible one. The bulb is likely burned out (most frequent cause) is the best explanation because it's the most common, simplest, or most likely cause.
abduction, best-explanation, diagnosis

Question 6

Given these logical premises: • If P, then Q • If Q, then R • If R, then S • Not S Which statement must be true?
This requires multi-step logical deduction:
• If P, then Q
• If Q, then R
• If R, then S
• Not S

Applying logical rules (modus ponens, modus tollens, contrapositive, transitive property, quantifier logic), we can conclude: Not P
multi-step, quantifier, modal

Question 7

Statistical finding: A drug trial with 500 patients found 80% improved. The control group had 30% improvement. What can you infer about the population?
This uses statistical inference: from a representative sample, we can make probabilistic claims about the population. The drug likely causes improvement (40% improvement over baseline is significant) is the appropriate inference, accounting for sampling error and confidence levels.
sampling, generalization, confidence

Question 8

Logical condition: Being a square is sufficient for being a rectangle. This shape is a square. What can you infer?
This tests necessary vs. sufficient conditions.

- If A is SUFFICIENT for B: A → B (A guarantees B, but B can happen without A)
- If A is NECESSARY for B: B → A (B cannot happen without A)

It is a rectangle
necessary-conditions, sufficient-conditions, logic

Question 9

Observation: Sales increased 40% after the advertising campaign What causal inference is most reasonable?
This inference uses temporal precedence (the cause occurred before the effect) and correlation to suggest causation: The advertising campaign likely caused increased sales

However, be aware of alternative explanations (confounding variables, regression to the mean, etc.) that might also explain the observation.
causation, temporal, correlation

Question 10

Quantifier logic: • All A are B • Some B are C • No C are D What can be inferred about the relationships?
This tests understanding of quantifiers (all, some, no, most). Some A may be C (but not necessarily)

Remember: 'Some' means 'at least one' (could be all). 'Most' means 'more than half'. No categorical statement about individuals follows from 'most' statements.
quantifiers, all-some-none, logic

Question 11

Consider these premises: • All doctors are educated • Some educated people are rich • Dr. Smith is a doctor Which conclusion logically follows?
By combining the premises logically:
• All doctors are educated
• Some educated people are rich
• Dr. Smith is a doctor

We can deduce: Dr. Smith is educated

This uses 3-step logical reasoning, applying transitive properties and categorical logic.
syllogism, chain-reasoning

Question 12

Given: If it snows, the roads become slippery. It is snowing. What can you logically conclude?
This is a direct inference. The conclusion follows necessarily from the premise: "If it snows, the roads become slippery. It is snowing." leads to "The roads are slippery" because the premise establishes a universal relationship and then confirms the condition.
direct, deductive, modus-ponens

Question 13

Analogical reasoning: "A government's budget should be managed like a household budget." What is the most reasonable inference by analogy?
This uses analogical reasoning: A government's budget should be managed like a household budget.

The analogy maps relationships from the source domain to the target domain, suggesting: Governments should avoid deficit spending just as households should

Analogical inferences are suggestive but not logically certain; the strength depends on the relevance and similarity of the mapped features.
analogy, metaphor, mapping

Question 14

Given: No reptiles are warm-blooded. A snake is a reptile. What can you logically conclude?
This is a direct inference. The conclusion follows necessarily from the premise: "No reptiles are warm-blooded. A snake is a reptile." leads to "A snake is not warm-blooded" because the premise establishes a universal relationship and then confirms the condition.
direct, deductive, modus-ponens

Question 15

Given: No reptiles are warm-blooded. A snake is a reptile. What can you logically conclude?
This is a direct inference. The conclusion follows necessarily from the premise: "No reptiles are warm-blooded. A snake is a reptile." leads to "A snake is not warm-blooded" because the premise establishes a universal relationship and then confirms the condition.
direct, deductive, modus-ponens

Question 16

Given these logical premises: • Either John or Mary broke the vase • If John broke it, he would admit it • John didn't admit it Which statement must be true?
This requires multi-step logical deduction:
• Either John or Mary broke the vase
• If John broke it, he would admit it
• John didn't admit it

Applying logical rules (modus ponens, modus tollens, contrapositive, transitive property, quantifier logic), we can conclude: Mary broke the vase
multi-step, quantifier, modal

Question 17

Analogical reasoning: "Students study to pass exams. Athletes train to win competitions." What is the most reasonable inference by analogy?
This uses analogical reasoning: Students study to pass exams. Athletes train to win competitions.

The analogy maps relationships from the source domain to the target domain, suggesting: Training serves the same preparatory function for athletes as studying does for students

Analogical inferences are suggestive but not logically certain; the strength depends on the relevance and similarity of the mapped features.
analogy, metaphor, mapping

Question 18

Analogical reasoning: "Neurons transmit signals in the brain like wires transmit electricity." What is the most reasonable inference by analogy?
This uses analogical reasoning: Neurons transmit signals in the brain like wires transmit electricity.

The analogy maps relationships from the source domain to the target domain, suggesting: Neurons form a biological wiring system for information transmission

Analogical inferences are suggestive but not logically certain; the strength depends on the relevance and similarity of the mapped features.
analogy, metaphor, mapping

Question 19

Statistical information: 95% of smokers who smoke for 20+ years develop respiratory issues. Bob has smoked for 25 years. What is the most reasonable inference?
This is probabilistic reasoning. The statistical evidence (95% of smokers who smoke for 20+ years develop respiratory issues. Bob has smoked for 25 years.) doesn't guarantee certainty, but it provides strong support for: Bob will likely develop respiratory issues

Remember: Probability inferences are about likelihood, not certainty.
probabilistic, statistical, likelihood

Question 20

Statistical information: 80% of startups fail within 3 years. Alex just started a company. What is the most reasonable inference?
This is probabilistic reasoning. The statistical evidence (80% of startups fail within 3 years. Alex just started a company.) doesn't guarantee certainty, but it provides strong support for: Alex's company will probably fail within 3 years

Remember: Probability inferences are about likelihood, not certainty.
probabilistic, statistical, likelihood
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