Anecdotal evidence<\/p>\n
A piece of biased evidence, usually drawn from personal experience, used to support a conclusion that may or may not be correct.<\/p>\n
Causality<\/p>\n
In research, the determination that one variable causes\u2014is responsible for\u2014an effect.<\/p>\n
Correlation<\/p>\n
In statistics, the measure of relatedness of two or more variables.<\/p>\n
Data (also called observations)<\/p>\n
In research, information systematically collected for analysis and interpretation.<\/p>\n
Deductive reasoning<\/p>\n
A form of reasoning in which a given premise determines the interpretation of specific observations (e.g., All birds have feathers; since a duck is a bird, it has feathers).<\/p>\n
Distribution<\/p>\n
In statistics, the relative frequency that a particular value occurs for each possible value of a given variable.<\/p>\n
Empirical<\/p>\n
Concerned with observation and\/or the ability to verify a claim.<\/p>\n
Fact<\/p>\n
Objective information about the world.<\/p>\n
Falsify<\/p>\n
In science, the ability of a claim to be tested and\u2014possibly\u2014refuted; a defining feature of science.<\/p>\n
Generalize<\/p>\n
In research, the degree to which one can extend conclusions drawn from the findings of a study to other groups or situations not included in the study.<\/p>\n
Hypothesis<\/p>\n
A tentative explanation that is subject to testing.<\/p>\n
Induction<\/p>\n
To draw general conclusions from specific observations.<\/p>\n
Inductive reasoning<\/p>\n
A form of reasoning in which a general conclusion is inferred from a set of observations (e. g., noting that \u201cthe driver in that car was texting; he just cut me off then ran a red light!\u201d (a specific observation), which leads to the general conclusion that texting while driving is dangerous).<\/p>\n
Levels of analysis<\/p>\n
In science, there are complementary understandings and explanations of phenomena.<\/p>\n
Null-hypothesis significance testing (NHST)<\/p>\n
In statistics, a test created to determine the chances that an alternative hypothesis would produce a result as extreme as the one observed if the null hypothesis were actually true.<\/p>\n
Objective<\/p>\n
Being free of personal bias.<\/p>\n
Population<\/p>\n
In research, all the people belonging to a particular group (e.g., the population of left handed people).<\/p>\n
Probability<\/p>\n
A measure of the degree of certainty of the occurrence of an event.<\/p>\n
Probability values<\/p>\n
In statistics, the established threshold for determining whether a given value occurs by chance.<\/p>\n
Pseudoscience<\/p>\n
Beliefs or practices that are presented as being scientific, or which are mistaken for being scientific, but which are not scientific (e.g., astrology, the use of celestial bodies to make predictions about human behaviors, and which presents itself as founded in astronomy, the actual scientific study of celestial objects. Astrology is a pseudoscience unable to be falsified, whereas astronomy is a legitimate scientific discipline).<\/p>\n
Representative<\/p>\n
In research, the degree to which a sample is a typical example of the population from which it is drawn.<\/p>\n
Sample<\/p>\n
In research, a number of people selected from a population to serve as an example of that population.<\/p>\n
Scientific theory<\/p>\n
An explanation for observed phenomena that is empirically well-supported, consistent, and fruitful (predictive).<\/p>\n
Type I error<\/p>\n
In statistics, the error of rejecting the null hypothesis when it is true.<\/p>\n
Type II error<\/p>\n
In statistics, the error of failing to reject the null hypothesis when it is false.<\/p>\n
Value<\/p>\n
Belief about the way things should be.<\/p>\n
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