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  2. Lists of statistics topics - Wikipedia

    en.wikipedia.org/wiki/Lists_of_statistics_topics

    List of unsolved problems in statistics; Probability. Topic outline of probability; List of probability topics. Catalog of articles in probability theory;

  3. Microsoft PowerPoint - Wikipedia

    en.wikipedia.org/wiki/Microsoft_PowerPoint

    Microsoft Producer for PowerPoint 2003" was a free plug-in from Microsoft, using a video camera, "that creates Web page presentations, with talking head narration, coordinated and timed to your existing PowerPoint presentation" for delivery over the web. [244]

  4. List of statistics articles - Wikipedia

    en.wikipedia.org/wiki/List_of_statistics_articles

    Jackknife (statistics) – redirects to Resampling (statistics) Jackson network; Jackson's theorem (queueing theory) Jadad scale; James–Stein estimator; Jarque–Bera test; Jeffreys prior; Jensen's inequality; Jensen–Shannon divergence; JMulTi – software; Johansen test; Johnson SU distribution; Joint probability distribution; Jonckheere's ...

  5. Statistics - Wikipedia

    en.wikipedia.org/wiki/Statistics

    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.

  6. Category:Template-Class Statistics pages - Wikipedia

    en.wikipedia.org/wiki/Category:Template-Class...

    Template talk:Baseball roster pitching statistics legend; Template talk:Basketball Champions League player statistics start; Template talk:Basketball player statistics; Template talk:Basketball player statistics row; Template talk:Basketball roster statistics full/footer; Template talk:Basketball roster statistics full/row; Template talk ...

  7. Statistical classification - Wikipedia

    en.wikipedia.org/wiki/Statistical_classification

    Algorithms of this nature use statistical inference to find the best class for a given instance. Unlike other algorithms, which simply output a "best" class, probabilistic algorithms output a probability of the instance being a member of each of the possible classes. The best class is normally then selected as the one with the highest probability.

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