Academic usage- significant!
can you give me a list of phrases that mean something different in academic language from their usual meaning eg full employment, inflation, statistically significant
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ChatGPT
Sure! Here’s a list of phrases that have specific meanings in academic or technical contexts that differ from their everyday usage:
Full Employment: In economics, this means all available labor resources are being used efficiently, not just that everyone has a job.
Inflation: While it often refers to rising prices in everyday language, academically, it specifically describes the rate at which the general level of prices for goods and services rises.
Statistically Significant: In common language, it might imply something important or noteworthy, but in statistics, it means that a result is unlikely to have occurred by chance, often at a predetermined threshold (e.g., p < 0.05).
Hypothesis: In casual conversation, it can mean a guess or assumption, but in scientific contexts, it refers to a testable statement about the relationship between variables.
Correlation: Commonly, it may imply a direct relationship, but in statistics, it simply indicates that two variables change together, without implying causation.
Variable: In everyday use, it can refer to anything that changes, but in research, it specifically denotes a measurable characteristic that can take on different values.
Sample Size: While it may seem to refer to the size of a sample in general terms, in statistics, it specifically denotes the number of observations or data points used in a study.
Peer Review: Generally means receiving feedback from others, but in academia, it specifically refers to the evaluation of research by experts in the same field before publication.
Theoretical Framework: Outside academia, it might mean a general idea, but it in research, it refers to the structure that can support or guide the research process.
Significance Level: In everyday use, this could imply importance, but in statistics, it defines the threshold at which you decide whether a result is statistically significant (commonly set at 0.05).