Critical Thinking Glossary

The CT Glossary is a list of standardized terms addressing the four elements of critical thinking: concepts, skills, ethics, and barriers. By creating a standard nomenclature, the elements of CT can be reinforced across contexts and learning can be transferred across subjects.

Our glossary is in its infancy and we invite visitors to add new entries and enhance existing ones. CT Foundry curates this glossary and will modify contributions as necessary to ensure accurate, standardized, and non-redundant entries.

Format of Entries
Entries in the CT glossary should be organized into the following sections. See existing entries for examples of proper formatting.

Term
Required. Generally one or two words. Sub-heading 1 level.

The standard term to be used to label the concept, skill, ethic, or barrier being described. This term is intended to be used across contexts and subject areas and so must be both descriptive and general enough to apply across domains. The term for any given entry may change over time as better versions of it are identified. Terms should be placed alphabetically within their respective group (concept, skill, ethic, or barrier).

Definition
Required. Simple English. Paragraph level. Should follow on next line after Term.

All entries should include a concise and accurate definition. Examples illustrating the term being defined are always helpful.

Synonyms
When applicable. Comma-separated list. Paragraph-level. Should be preceded by "Synonyms" on a separate line above it with a sub heading 2 level.

As part of our goal to establish a standard set of terms, we wish to avoid redundant entries in the CT Glossary. Therefore, when there is more than one term for a given entry, alternative terms should be listed as synonyms. For example, while "Prevalence" is another way to describe "Base Rate", we have an entry only for "Base Rate" and specify "Prevalence" as a synonym.

Concepts
Good critical thinking requires understanding certain concepts. Some can be simple, others complex.

Absolute Risk
The chances that something will occur in a given group. For example, the chances of being struck by lightning in the United States in a given year is 1 in 700,000. Compare to relative risk, which compares the chances that something will occur in one group relative to another group. For example, the relative risk of lightning strike for males is about three times greater than the risk for females, but it is still very low in terms of absolute risk.

Base Rate
The frequency that something occurs or is true within a given group. For example, about 14% of all people in the US have a first name that begins with "A", meaning that the base rate of names that begin with "A" in the US at this time is 14%, or about one in every seven people.

Claim
Saying that something is true.

Fact
Anything that is true for everyone.

Objective Claim
A claim that must be either true for everyone or false for everyone. A claim that something is a fact. For example, saying that the the Earth is flat is an objective claim because it must be either true for everyone or false for everyone. It cannot be true for some people and false for others. All objective claims can be evaluated as either probably true, probably false, or not enough information to say. Compare with subjective claim.

Random Sample
A sample that is chosen in a way that there is an equal chance that any part of the thing being sampled is picked. Random samples are more likely to accurately tell us what the whole is like than are non-random samples.

Relative Risk
The chances of something occurring in one group compared to another. For example, if color-blindness occurs in eight percent of all men and one-half of a percent in all women, then the relative risk of men having color-blindness compared to women is 1,600 percent. In other words, men are 16 times more likely to be color blind than women. Compare to absolute risk.

Remembered evidence
Evidence recalled from memory. Compare with recorded evidence and physical evidence.

Sample
A small part of something that is supposed to show what the whole thing is like.

Sample Size
The number of items in a sample. The larger the sample size, the more confident we can be that the sample is the same as the whole thing that it came from.

Sound Method
A method can be more or less sound, depending on how much of each of the following characteristics:


 * Clear (easily understood)
 * Concise (no extra steps, no steps left out)
 * Repeatable (can be performed by other people at other times)
 * Recorded (written down or captured via audio or video so that doing it does not rely on memory)
 * Complete (works for all cases).

Subjective Claim
A claim that can be true for some people and false for others at the same time. For example, "Cats are better than dogs" is a subjective claim because it can be both true for some people and false for other people at the same time.

Skills
Skills are the abilities required for good critical thinking. With sufficient practice, skills can become habits.

Ethics
Good critical thinking also involves adopting certain ethics.

Barriers
We all encounter barriers to critical thinking. Recognizing these barriers is key to good critical thinking.

Appeal to Hypocrisy
A logical error where a claim of wrongdoing is refuted by asserting that others have done the same thing. For example, arguing that it is acceptable to steal because others have stolen as well.

Argument from Authority
A claim that something is true just because a person, book, or other source says it is true. Arguments from authority are very weak support for a claim unless what the authority says is in turn based on good evidence and reasoning.

Argument from Ignorance
A claim that something is true because it has not yet been proven false. This is a logical error because one can make a claim about anything that has not yet been proven false, like "There is life on the planet Saturn." Just making a claim that has not or cannot be proven false does not in any way make it true.

Base Rate Fallacy
Forgetting to consider the base rate of a given event or characteristic when considering its probability in a given instance. This error can lead to false conclusions. For example, if I guessed that you had a close family member whose first name began with an "A" or a "J" (which is true for about 25% of the US population), thinking that it was an extremely lucky guess, or that I had special powers, would be an example of the base rate fallacy. Alternatively, if a positive test result for a disease is correct 95% of the time, but the disease only occurs in 1 out of every 1,000 people, it would be a base rate fallacy to conclude that a person with a positive test result is likely to have the disease since, because of the disease's low base rate, a positive result still means that there is less than a 2% chance the person actually has the disease.

Confirmation Bias
Looking for or remembering only the evidence that supports a claim and not looking for or remembering the evidence the refutes it. For example, you remember looking at a clock a number of times recently and seeing 10:12 each time, which is your birthday. You therefore conclude there is something special going on when really, you just don't remember all the times you looked at the clock and saw something other than 10:12.

Causation Fallacy
Thinking that A causes B because A happens before or together with B. For example, thinking that a rooster crowing every morning causes the sun to rise.

Conspiracy Fallacy
Thinking that the reason there is a lack of evidence for a claim is because there is a conspiracy to cover it up.

False Equivalence
Treating the evidence for a claim as equal to evidence against it, or vice versa, even though it is not. For example, claiming that because some people hold that the Earth is at the center of the solar system, we cannot say it is probably true that the sun is actually at the center.

Lottery Fallacy
Mistakenly thinking that because something is unlikely to happen to a single person or in a single instance it is unlikely to happen among multiple people or multiple instances. For example, while it is unlikely after any given dream about someone you know that they will call you next day, if you have enough dreams about people you know, it's likely that at some point, the person you just dreamt about will call you. This is called the lottery fallacy because even though the chances of any one person winning the lottery is tiny, the chances that someone will win the lottery are large.