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Inference - Beginner-Intermediate Level: probable inference BEGINNER-INTERMEDIATE

Ready to master inference? This benchmark test features 20 beginner-intermediate-level challenges. Worksheet 12 of 30 sharpens your probable inference skills. Master inferential logic, hidden meanings, implicit information through guided practice. Perfect for developing test preparation.

📝 Worksheet 12 of 30 • 20 questions • ⏱️ Estimated time: 20 minutes • 🎯 Beginner-intermediate level

What you'll learn in this worksheet:
Your progress through Inference
Worksheet 12 of 30 (40% complete)

Question 1

Statistical finding: Of 50 randomly selected days, 40 were sunny. The region has 365 days per year. What can you infer about the population?
This uses statistical inference: from a representative sample, we can make probabilistic claims about the population. Approximately 292 days per year are sunny in this region (80% of days) is the appropriate inference, accounting for sampling error and confidence levels.
sampling, generalization, confidence

Question 2

Consider these premises: • If you practice daily, you improve • If you improve, you win matches • Sarah practices daily Which conclusion logically follows?
By combining the premises logically:
• If you practice daily, you improve
• If you improve, you win matches
• Sarah practices daily

We can deduce: Sarah will win matches

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

Question 3

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

Question 4

Rule: If you exercise regularly, you stay healthy Observation: John is not healthy What can you logically infer?
This uses the contrapositive rule. The statement "If you exercise regularly, you stay healthy" is logically equivalent to its contrapositive: 'If NOT consequence, then NOT condition.' Since we observe "John is not healthy" (the consequence is false), we can conclude "John doesn't exercise regularly" (the condition is false).
contrapositive, modus-tollens

Question 5

Quantifier logic: • Most students passed math • Most students passed science What can be inferred about the relationships?
This tests understanding of quantifiers (all, some, no, most). Some students passed both subjects

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 6

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 7

Given these logical premises: • All birds can fly • Penguins are birds but cannot fly • This statement is about typical birds • Tweety is a typical bird Which statement must be true?
This requires multi-step logical deduction:
• All birds can fly
• Penguins are birds but cannot fly
• This statement is about typical birds
• Tweety is a typical bird

Applying logical rules (modus ponens, modus tollens, contrapositive, transitive property, quantifier logic), we can conclude: Tweety can fly
multi-step, quantifier, modal

Question 8

Observation: The car won't start. Possible causes: dead battery, empty gas tank, starter problem, or electrical issue. Which is the most reasonable inference about the cause?
This is abductive reasoning (inference to the best explanation). Given the observation 'The car won't start. Possible causes: dead battery, empty gas tank, starter problem, or electrical issue.', we consider possible causes and select the most plausible one. The battery is probably dead (most common cause) is the best explanation because it's the most common, simplest, or most likely cause.
abduction, best-explanation, diagnosis

Question 9

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 10

Observation: Patient recovery times shortened after the new treatment was introduced What causal inference is most reasonable?
This inference uses temporal precedence (the cause occurred before the effect) and correlation to suggest causation: The new treatment likely accelerated recovery

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

Question 11

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 12

Given: All birds have wings. A sparrow is a bird. What can you logically conclude?
This is a direct inference. The conclusion follows necessarily from the premise: "All birds have wings. A sparrow is a bird." leads to "A sparrow has wings" because the premise establishes a universal relationship and then confirms the condition.
direct, deductive, modus-ponens

Question 13

Consider this argument: "Most successful entrepreneurs dropped out of college. If you want to be successful, you should drop out." What unstated assumption must be true for this reasoning to be valid?
The argument makes a hidden assumption: College education prevents success (and the correlation represents causation)

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 14

Observation: The patient has a fever and cough. Possible diagnoses: common cold, flu, COVID-19, or pneumonia. Which is the most reasonable inference about the cause?
This is abductive reasoning (inference to the best explanation). Given the observation 'The patient has a fever and cough. Possible diagnoses: common cold, flu, COVID-19, or pneumonia.', we consider possible causes and select the most plausible one. The flu is a likely diagnosis (given typical seasonal presentation) is the best explanation because it's the most common, simplest, or most likely cause.
abduction, best-explanation, diagnosis

Question 15

Rule: If you water plants, they grow Observation: The plants didn't grow What can you logically infer?
This uses the contrapositive rule. The statement "If you water plants, they grow" is logically equivalent to its contrapositive: 'If NOT consequence, then NOT condition.' Since we observe "The plants didn't grow" (the consequence is false), we can conclude "They weren't watered" (the condition is false).
contrapositive, modus-tollens

Question 16

Statistical information: 7 out of 10 doctors recommend this medication. Your doctor prescribed it. What is the most reasonable inference?
This is probabilistic reasoning. The statistical evidence (7 out of 10 doctors recommend this medication. Your doctor prescribed it.) doesn't guarantee certainty, but it provides strong support for: This medication is probably effective

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

Question 17

Statistical information: The probability of rain given dark clouds is 85%. The sky has dark clouds. What is the most reasonable inference?
This is probabilistic reasoning. The statistical evidence (The probability of rain given dark clouds is 85%. The sky has dark clouds.) doesn't guarantee certainty, but it provides strong support for: It will probably rain

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

Question 18

Observation: Patient recovery times shortened after the new treatment was introduced What causal inference is most reasonable?
This inference uses temporal precedence (the cause occurred before the effect) and correlation to suggest causation: The new treatment likely accelerated recovery

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

Question 19

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 20

Quantifier logic: • No reptiles have fur • All snakes are reptiles • Some pets are snakes What can be inferred about the relationships?
This tests understanding of quantifiers (all, some, no, most). Some pets do not have fur

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
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