Portal:Statistics
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Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities, government and business.
Statistical methods can be used to summarize or describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics. Both descriptive and inferential statistics comprise applied statistics. There is also a discipline called mathematical statistics, which is concerned with the theoretical basis of the subject.
The word statistics is also the plural of statistic (singular), which refers to the result of applying a statistical algorithm to a set of data, as in economic statistics, crime statistics, etc.
The margin of error is usually defined as the radius of a confidence interval for a particular statistic from a survey. One example is the percent of people who prefer product A versus product B. When a single, global margin of error is reported for a survey, it refers to the maximum margin of error for all reported percentages using the full sample from the survey. If the statistic is a percentage, this maximum margin of error can be calculated as the radius of the confidence interval for a reported percentage of 50%.
The margin of error has been described as an "absolute" quantity, equal to a confidence interval radius for the statistic. For example, if the true value is 50 percentage points, and the statistic has a confidence interval radius of 5 percentage points, then we say the margin of error is 5 percentage points. As another example, if the true value is 50 people, and the statistic has a confidence interval radius of 5 people, then we might say the margin of error is 5 people.
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- ...that as a graduate student at UC Berkeley in 1939, George Dantzig solved two then-unanswered questions related to the Neyman-Pearson lemma, because he mistakenly thought they were a homework assignment?
- ...that one result of the birthday problem is that among a group of 23 (or more) randomly chosen people, there is more than 50% probability that some pair of them will both have been born on the same day of the year?
- ...that the term bias is not necessarily pejorative in statistics, since biased estimators may have desirable properties (such as a smaller mean squared error than any unbiased estimator), and that in extreme cases the only unbiased estimators are not even within the convex hull of the parameter space?
- ...that William Sealy Gosset published under the pseudonym Student in order to avoid detection by his employer, and so his most famous achievement is now referred to as Student's t-distribution, which might otherwise have been Gosset's t-distribution?
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