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  2. Power Pivot - Wikipedia

    en.wikipedia.org/wiki/Power_Pivot

    Power Pivot can scale to process very large datasets in memory, which allows users to analyze datasets that would otherwise surpass Excel's limit of one million rows. [9] Power Pivot allows for importing data from multiple sources, such as databases (SQL Server, Microsoft Access, etc.), OData data feeds, Excel files, and other sources ...

  3. Pick chart - Wikipedia

    en.wikipedia.org/wiki/Pick_chart

    PICK charts are a method to prioritize a number of action items or problem solving ideas. A pick chart allows visual comparison of action items relative to their impact to the problem being addressed vs. the ease/cost of implementation. In VERY rudimentary terms, PICK charts are a Return On Investment (ROI) method.

  4. Data set - Wikipedia

    en.wikipedia.org/wiki/Data_set

    Various plots of the multivariate data set Iris flower data set introduced by Ronald Fisher (1936). [1]A data set (or dataset) is a collection of data.In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question.

  5. Wide and narrow data - Wikipedia

    en.wikipedia.org/wiki/Wide_and_narrow_data

    Many statistical and data processing systems have functions to convert between these two presentations, for instance the R programming language has several packages such as the tidyr package.

  6. Posterior probability - Wikipedia

    en.wikipedia.org/wiki/Posterior_probability

    Posterior probability is a conditional probability conditioned on randomly observed data. Hence it is a random variable. For a random variable, it is important to summarize its amount of uncertainty. One way to achieve this goal is to provide a credible interval of the posterior probability. [11]

  7. Multivariate random variable - Wikipedia

    en.wikipedia.org/wiki/Multivariate_random_variable

    Formally, a multivariate random variable is a column vector = (, …,) (or its transpose, which is a row vector) whose components are random variables on the probability space (,,), where is the sample space, is the sigma-algebra (the collection of all events), and is the probability measure (a function returning each event's probability).

  8. Frequency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Frequency_(statistics)

    A frequency distribution shows a summarized grouping of data divided into mutually exclusive classes and the number of occurrences in a class. It is a way of showing unorganized data notably to show results of an election, income of people for a certain region, sales of a product within a certain period, student loan amounts of graduates, etc.

  9. Variable and attribute (research) - Wikipedia

    en.wikipedia.org/wiki/Variable_and_attribute...

    In data processing data are often represented by a combination of items (objects organized in rows), and multiple variables (organized in columns). Values of each variable statistically "vary" (or are distributed) across the variable's domain. A domain is a set of all possible values that a variable is allowed to have.