PHIL 347 Week 6 Checkpoint
Student Name
Chamberlain University
PHIL-347: Critical Reasoning
Prof. Name
Date
Week 6 Checkpoint
Question 1 — What are the three fundamental reasoning strategies listed in the text?
Answer
The text identifies three primary modes of reasoning: comparative reasoning, ideological reasoning, and empirical reasoning.
- Comparative reasoning draws conclusions by highlighting similarities and differences between two (or more) items, situations, or events.
- Ideological reasoning (sometimes called doctrinal or theoretical reasoning) uses a framework of values, principles, or theories to interpret facts and justify conclusions.
- Empirical reasoning relies on observation, measurement, and data — it builds inferences from evidence that can be tested and (ideally) independently verified.
| Strategy | Core idea | Typical use / example |
|---|---|---|
| Comparative reasoning | Inference by analogy or contrast | Explaining why one business strategy may work by comparing it to a similar historical case |
| Ideological reasoning | Interpreting facts through a value/theory lens | Arguing policy from a libertarian or utilitarian framework |
| Empirical reasoning | Drawing conclusions from observed data | Concluding a drug is effective based on clinical trial results |
Question 2 — What is comparative reasoning? On what skill is it based?
Answer
Comparative reasoning is a way of thinking that reaches conclusions by comparing two or more things — asking how they are alike in relevant respects and how they differ. It is fundamentally an analogical process: we use what we know about a familiar case to make inferences about a less familiar one. This form of reasoning depends heavily on critical thinking skills: identifying which similarities matter (relevance), spotting important differences (disanalogies), and judging whether the analogy supports the conclusion. Good comparative reasoning requires not only noticing surface resemblances, but also evaluating causal or structural parallels that genuinely bear on the question at hand.
Question 3 — We learned four tests for evaluating arguments: truthfulness of the premises, logical strength, relevance, and non-circularity. How well do these tests work with respect to evaluating comparative reasoning? Consider each of the four tests.
Answer
Each of the four classic tests can be applied to analogical or comparative arguments, but they often require reinterpretation or additional checks to be useful. The table below summarizes how each test applies and what special considerations comparative reasoning introduces.
PHIL 347 Week 6 Checkpoint
| Test | What the test normally asks | How it applies to comparative reasoning | Limitations & extra checks |
|---|---|---|---|
| Truthfulness of premises | Are the factual claims in the premises accurate? | For comparisons, this means checking the factual claims about both the familiar and the unfamiliar cases (e.g., “X had feature A”) | Analogies often rest on relational or interpretive claims rather than simple true/false facts. You must verify the empirical facts and the reported similarities/differences. |
| Logical strength | Do the premises provide good support for the conclusion? | Analogical inferences are inductive: strength depends on number, relevance, and independence of similarities and on absence of crucial dissimilarities | Strength must be judged probabilistically — more and more relevant similarities → stronger analogy. Look for counterexamples and assess how typical the similarities are. |
| Relevance | Are the premises connected to the conclusion in the right way? | This is central for analogies: only similarities that matter to the conclusion are relevant | The arguer must justify why a given similarity is relevant (mechanism, causal link, structural parallel). Otherwise the analogy can be persuasive but misleading. |
| Non-circularity | Does the argument assume what it tries to prove? | Analogies can become circular if the analogy presupposes the conclusion (e.g., using the conclusion’s perspective to select similarities) | Check whether the analogical claim depends on hidden assumptions that already imply the conclusion. Seek independent grounds for the analogy. |
Overall assessment: The four tests are still useful but they need tailoring. Comparative reasoning benefits from extra criteria (see Q4) — especially careful scrutiny of relevance and of disanalogies — because analogies are probabilistic and sensitive to context. In practice, you should combine these tests with domain knowledge and explicit justification of why the chosen similarities matter.
Question 4 — What are the five criteria for evaluating comparative reasoning? Name and define them in your own words.
Answer
Below are the five widely used criteria for judging the quality of a comparison, restated and expanded with short examples.
| Criterion | Definition (in my own words) | Why it matters / Example |
|---|---|---|
| Familiarity | How well the audience understands the familiar case used in the analogy. | If listeners know the comparison case well, they can better judge whether the analogy fits; otherwise the analogy can mislead. |
| Simplicity | How straightforward and uncluttered the comparison is — few, clear points of comparison rather than many messy distinctions. | Simple analogies are easier to evaluate and less likely to hide relevant dissimilarities. |
| Comprehensiveness | The extent to which the comparison covers the key, relevant features rather than just a narrow slice. | A comparison that attends to most relevant dimensions (not just convenient ones) is more trustworthy. |
| Productivity | Whether the analogy generates useful new questions, hypotheses, or predictions beyond the immediate claim. | A productive analogy suggests further testable consequences or helps solve problems in the new case. |
| Testability | The degree to which the analogy leads to predictions or consequences that can be empirically checked and potentially falsified. | Testable analogies can be validated or overturned by evidence (stronger than purely rhetorical analogies). |
These criteria help move an analogy from being merely rhetorically attractive to being epistemically valuable.
Question 5 — According to the text, the basic question to ask when evaluating a comparison between two objects or ideas or events is “Are they alike enough in the important ways or not?” (p. 248). What are those “important ways” that determine the credibility of conclusions based on similarities?
Answer
The “important ways” are the features or relationships that are causally or structurally relevant to the conclusion you want to draw. Key elements include:
- Causal relevance: Do the shared features play a causal role in producing the outcome in the familiar case? If yes, similarity is more persuasive.
- Number and depth of similarities: Multiple independent similarities that point to the same mechanism strengthen the analogy.
- Absence of critical dissimilarities: A single major disanalogy can vitiate the analogy even if many small similarities exist.
- Contextual and temporal similarity: Situational factors (time period, scale, institutional settings) must match where they matter.
- Theoretical support: Existing theory or mechanisms that link the similarities to the outcome add credibility (not just surface resemblance).
In short: similarities matter only when they are relevant to what you are trying to explain or predict.
(See the textbook’s formulation on p. 248 for the basic diagnostic question.)
Question 6 — In your own words, define empirical reasoning.
Answer
Empirical reasoning is drawing conclusions from observations, measurements, or experiments. It is an evidence-based mode of inference: claims rest on data collected from the world, and those claims are judged by how well the data support them. Empirical reasoning is characteristically inductive (it generalizes from instances), self-correcting (updatable when new evidence appears), and open to independent verification (others can check the observations and analyses).
Question 7 — What are the three defining characteristics of empirical reasoning?
Answer
- Inductive: Empirical reasoning moves from particular observations to general conclusions (probabilistic, not deductive certainty).
- Self-correcting: Conclusions are provisional and revised in light of new evidence or better analyses.
- Open to independent verification (replicability): Other investigators should be able to reproduce methods and results; transparency of method and data is essential.
Question 8 — What is meant by “the null hypothesis”?
Answer
The null hypothesis is the default claim used in empirical testing that there is no systematic effect or relationship between the variables of interest — any observed association is attributable to chance or sampling variability. It provides a baseline that the data must convincingly contradict before we accept an alternative hypothesis. Importantly, rejecting the null suggests a non-random pattern but does not by itself prove a causal mechanism.
Question 9 — What is the purpose of empirical reasoning?
Answer
Empirical reasoning aims to explain, predict, and sometimes control phenomena by grounding claims in observable evidence. It provides a systematic way to test hypotheses, build cumulative knowledge, and inform decisions and policy. Because it emphasizes testability and replication, empirical reasoning helps distinguish well-supported claims from speculation.
Question 10 — How do we evaluate empirical reasoning?
Answer
Empirical reasoning is evaluated on multiple fronts: the quality of data and measurement, the soundness of the design, the correctness of the analysis, and the plausibility of the inferences. Alongside the four classic argument tests (truthfulness of premises, logical strength, relevance, and non-circularity), empirical work is judged by standards such as internal validity, external validity, statistical robustness, transparency, and reproducibility.
PHIL 347 Week 6 Checkpoint
| Evaluation focus | What you check | Why it matters |
|---|---|---|
| Measurement validity | Do the instruments actually measure the constructs of interest? | Poor measures produce misleading results. |
| Internal validity | Are alternative explanations (confounders, bias) ruled out? | Necessary for causal claims. |
| External validity | Can results generalize beyond the sample/context? | Determines applicability. |
| Statistical analysis | Are the methods appropriate and assumptions met? | Misapplied stats can produce false positives/negatives. |
| Transparency & replication | Are methods, data, and code available so others can reproduce findings? | Enhances trust and correction of errors. |
| Peer review & replication | Has the work been reviewed and independently replicated? | Reduces likelihood of errors or fraud. |
Peer review and independent replication are especially important because published empirical claims can still contain methodological errors or selective reporting.
Question 11 — What part of a research design addresses the test for logical strength, and how is it addressed?
Answer
The analysis and interpretation phases of research — together with the study’s design choices — address logical strength. Logical strength here means that the evidence, as collected and analyzed, provides dependable support for the conclusion. Researchers build logical strength by:
- Designing studies that produce data directly relevant to the hypothesis (operationalization).
- Using controls, randomization, or statistical adjustments to reduce confounding (improves internal validity).
- Selecting appropriate statistical tests and reporting effect sizes and uncertainty (presents the strength of evidence).
- Demonstrating that the hypothesized causal mechanism plausibly links the evidence to the conclusion (theoretical grounding).
Put simply: research design creates the conditions for strong inductive inferences; the data analysis then connects those data to the claimed conclusion with transparent reasoning.
Question 12 — Briefly explain the process of peer review. What is the process of peer review designed to do?
Answer
Process (typical flow):
- Submission: Author sends manuscript to a journal.
- Editorial screening: Editor checks scope and basic standards.
- Reviewer assignment: Editor sends the manuscript to several expert reviewers.
- Review: Reviewers assess methods, logic, evidence, originality, and ethics — and recommend accept, revise, or reject.
- Revision: Authors revise in response to reviewers’ criticisms.
- Decision & publication: Editor decides based on reviews and revisions.
Purpose: Peer review is intended to act as a quality-control mechanism: to detect methodological flaws, logical errors, ethical problems, and unsupported claims; to improve clarity; and to screen out work that fails to meet disciplinary standards. It is not infallible — biases and oversights occur — but it remains a central mechanism for improving and vetting scholarly claims.
Question 13 — The authors of our text state: “We have 40 years of data across multiple studies that confirm the positive correlation between taking a course in critical thinking and improvements in the students’ pretest to post-test critical thinking skills scores. It would be a mistake, therefore, all things being equal, to say that growth in critical thinking and taking a course in critical thinking are unrelated” (p. 290). The null hypothesis is false. Does that mean, therefore, that taking a critical thinking course causes students to become more skilled at critical thinking and more motivated to use those skills? Explain your answer.
Answer
No — rejection of the null hypothesis (i.e., finding a reliable correlation) does not automatically prove causation. Correlation shows a systematic relationship, but causal inference requires additional evidence:
- Temporal precedence: Did the course come before the gains? (Pre-post design helps here.)
- Rule out confounders: Could factors like student motivation, instructor quality, selection effects (students who choose the course), or concurrent experiences explain the gains?
- Mechanism: Is there a plausible instructional mechanism linking the course to the observed improvement?
- Experimental evidence: Randomized controlled trials (or natural experiments) that assign students to course vs. control strengthen causal claims.
Forty years of correlational evidence make the association credible and worth investigating, but to claim causality you need designs or analyses that address confounding, demonstrate temporal order, and provide plausible mechanisms (see p. 290). Where randomized experiments are not available, stronger causal inference can come from longitudinal designs, statistical controls, instrumental variables, or replication across contexts.
Question 14 — If reasoning is empirical, contains statistics, and appears in print, should we take for granted that it has passed the four tests of truthfulness of the premises, logical strength, relevance, and non-circularity? Explain your answer.
Answer
No — publication and the presence of statistics do not guarantee that an argument has passed the four tests. Published empirical work can still suffer from measurement error, poor design, inappropriate analysis, selective reporting, p-hacking, or logical gaps (e.g., inferring causation from correlation). Therefore, readers should evaluate empirical claims critically: check the data sources, methods, assumptions, robustness checks, and whether independent replication exists. Peer review reduces some risks, but it is not a guarantee; critical scrutiny and attempts at replication are essential to confirm that the claims meet the four tests in practice.