PHIL 347 WEEK 6 CHECKPOINT CRITICAL
THINKING EXAM AMERICAN PUBLIC UNIVERSITY
- NEW SOLUTION 2026.
DOMAIN 1: INDUCTIVE REASONING & STATISTICAL FALLACIES (8 Questions)
Question 1 (Multiple-Choice)
A first-year student arrives on campus and has a single difficult interaction with a professor
who seems demanding and strict. The student immediately posts on social media: "All
professors at this university are impossible to please. Avoid this school at all costs!" This
argument is an example of which fallacy?
A. Ad Hominem
B. Hasty Generalization
C. Straw Man
D. False Dilemma
Answer: B [CORRECT]
Rationale: This argument is a Hasty Generalization—a fallacy in which a broad conclusion ("All
professors at this university are impossible to please") is drawn from a sample that is far too
small (a single encounter with one professor on the first day of class). For a valid inductive
generalization about a university's faculty, the sample must be sufficiently large and
representative of the target population. A single interaction provides no statistical basis for
generalizing to hundreds of faculty members across dozens of departments. The student's
emotional reaction to one encounter has led to an unjustified universal claim.
Question 2 (Multiple-Choice)
A tourist visits one restaurant in a city, receives poor service, and concludes, "The food service
industry in this entire city is terrible. I'll never eat here again." What is the specific logical flaw
in this reasoning?
A. The argument confuses correlation with causation
B. The argument draws a universal conclusion from an insufficient sample size
C. The argument attacks the character of the restaurant staff
D. The argument assumes that all restaurants are identical
, Answer: B [CORRECT]
Rationale: The specific logical flaw is a Hasty Generalization—drawing a universal conclusion
about an entire city's food service industry from a single restaurant visit. For a valid inductive
generalization, the sample must be large enough and representative of the target population.
One restaurant out of potentially thousands provides statistically insignificant evidence. The
tourist has committed the error of extrapolating from an N=1 sample to an entire population,
violating the fundamental requirement that inductive strength depends on sample size
relative to population variability.
Question 3 (Select-All-That-Apply)
Which of the following are specific criteria that must be met for a statistical syllogism to be
considered strong and avoid sampling bias? (Select all that apply)
A. The sample must be large enough relative to the size and variability of the target
population
B. The sample must be randomly selected to ensure each member of the population has an
equal chance of inclusion
C. The sample must be representative of the relevant characteristics of the target population
D. The conclusion must be stated with absolute certainty
E. The sample should include only participants who support the researcher's hypothesis
F. The margin of error should be calculated and reported
Answer: A, B, C, F [CORRECT]
Rationale: A strong statistical syllogism requires: a sufficiently large sample (A) relative to
population size and variability to ensure statistical power; random selection (B) to prevent
selection bias and ensure generalizability; representativeness (C) so the sample mirrors the
target population's relevant demographic and characteristic distributions; and a reported
margin of error (F) to quantify the range of uncertainty around the sample statistic. Absolute
certainty (D) is impossible in inductive reasoning—statistical syllogisms yield probabilistic, not
deductive, conclusions. Including only supportive participants (E) creates confirmation bias
and invalidates the syllogism.
Question 4 (Multiple-Choice)
A political poll surveys 50 registered voters at a single shopping mall in an affluent suburb and
concludes that 78% of all voters in the state support a particular candidate. What is the
primary weakness of this statistical syllogism?
THINKING EXAM AMERICAN PUBLIC UNIVERSITY
- NEW SOLUTION 2026.
DOMAIN 1: INDUCTIVE REASONING & STATISTICAL FALLACIES (8 Questions)
Question 1 (Multiple-Choice)
A first-year student arrives on campus and has a single difficult interaction with a professor
who seems demanding and strict. The student immediately posts on social media: "All
professors at this university are impossible to please. Avoid this school at all costs!" This
argument is an example of which fallacy?
A. Ad Hominem
B. Hasty Generalization
C. Straw Man
D. False Dilemma
Answer: B [CORRECT]
Rationale: This argument is a Hasty Generalization—a fallacy in which a broad conclusion ("All
professors at this university are impossible to please") is drawn from a sample that is far too
small (a single encounter with one professor on the first day of class). For a valid inductive
generalization about a university's faculty, the sample must be sufficiently large and
representative of the target population. A single interaction provides no statistical basis for
generalizing to hundreds of faculty members across dozens of departments. The student's
emotional reaction to one encounter has led to an unjustified universal claim.
Question 2 (Multiple-Choice)
A tourist visits one restaurant in a city, receives poor service, and concludes, "The food service
industry in this entire city is terrible. I'll never eat here again." What is the specific logical flaw
in this reasoning?
A. The argument confuses correlation with causation
B. The argument draws a universal conclusion from an insufficient sample size
C. The argument attacks the character of the restaurant staff
D. The argument assumes that all restaurants are identical
, Answer: B [CORRECT]
Rationale: The specific logical flaw is a Hasty Generalization—drawing a universal conclusion
about an entire city's food service industry from a single restaurant visit. For a valid inductive
generalization, the sample must be large enough and representative of the target population.
One restaurant out of potentially thousands provides statistically insignificant evidence. The
tourist has committed the error of extrapolating from an N=1 sample to an entire population,
violating the fundamental requirement that inductive strength depends on sample size
relative to population variability.
Question 3 (Select-All-That-Apply)
Which of the following are specific criteria that must be met for a statistical syllogism to be
considered strong and avoid sampling bias? (Select all that apply)
A. The sample must be large enough relative to the size and variability of the target
population
B. The sample must be randomly selected to ensure each member of the population has an
equal chance of inclusion
C. The sample must be representative of the relevant characteristics of the target population
D. The conclusion must be stated with absolute certainty
E. The sample should include only participants who support the researcher's hypothesis
F. The margin of error should be calculated and reported
Answer: A, B, C, F [CORRECT]
Rationale: A strong statistical syllogism requires: a sufficiently large sample (A) relative to
population size and variability to ensure statistical power; random selection (B) to prevent
selection bias and ensure generalizability; representativeness (C) so the sample mirrors the
target population's relevant demographic and characteristic distributions; and a reported
margin of error (F) to quantify the range of uncertainty around the sample statistic. Absolute
certainty (D) is impossible in inductive reasoning—statistical syllogisms yield probabilistic, not
deductive, conclusions. Including only supportive participants (E) creates confirmation bias
and invalidates the syllogism.
Question 4 (Multiple-Choice)
A political poll surveys 50 registered voters at a single shopping mall in an affluent suburb and
concludes that 78% of all voters in the state support a particular candidate. What is the
primary weakness of this statistical syllogism?
