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Many misuses of statistics occur because The source is a subject matter expert, not a statistics expert. [6] The source may incorrectly use a method or interpret a result. The source is a statistician, not a subject matter expert. [7] An expert should know when the numbers being compared describe different things.
This is an abridged version of Teddi Fishman's definition of plagiarism, which proposed five elements characteristic of plagiarism. [57] According to Fishman, plagiarism occurs when someone: Uses words, ideas, or work products; Attributable to another identifiable person or source; Without attributing the work to the source from which it was ...
In statistics, an outlier is a data point that differs significantly from other observations. [1] [2] An outlier may be due to a variability in the measurement, an indication of novel data, or it may be the result of experimental error; the latter are sometimes excluded from the data set.
The scope of the discipline of statistics broadened in the early 19th century to include the collection and analysis of data in general. Today, statistics is widely employed in government, business, and natural and social sciences. Carl Friedrich Gauss made major contributions to probabilistic methods leading to statistics.
Detection bias occurs when a phenomenon is more likely to be observed for a particular set of study subjects. For instance, the syndemic involving obesity and diabetes may mean doctors are more likely to look for diabetes in obese patients than in thinner patients, leading to an inflation in diabetes among obese patients because of skewed detection efforts.
Though there are many approximate solutions (such as Welch's t-test), the problem continues to attract attention [4] as one of the classic problems in statistics. Multiple comparisons: There are various ways to adjust p-values to compensate for the simultaneous or sequential testing of hypotheses. Of particular interest is how to simultaneously ...
Some examples of statistics are: "In a recent survey of Americans, 52% of women say global warming is happening." In this case, "52%" is a statistic, namely the percentage of women in the survey sample who believe in global warming.
In statistics, identifiability is a property which a model must satisfy for precise inference to be possible. A model is identifiable if it is theoretically possible to learn the true values of this model's underlying parameters after obtaining an infinite number of observations from it.