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  2. Verification and validation of computer simulation models

    en.wikipedia.org/wiki/Verification_and...

    Comparing curves with fixed sample size tradeoffs between model builder's risk and model user's risk can be seen easily in the risk curves. [7] If model builder's risk, model user's risk, and the upper and lower limits for the range of accuracy are all specified then the sample size needed can be calculated. [7]

  3. Microsoft Power BI - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Power_BI

    The first release of Power BI was based on the Microsoft Excel-based add-ins: Power Query, Power Pivot and Power View. With time, Microsoft also added many additional features like question and answers, enterprise-level data connectivity, and security options via Power BI Gateways. [10] Power BI was first released to the general public on 24 ...

  4. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Cross-validation. By splitting the data into multiple parts, we can check if an analysis (like a fitted model) based on one part of the data generalizes to another part of the data as well. [ 144 ] Cross-validation is generally inappropriate, though, if there are correlations within the data, e.g. with panel data . [ 145 ]

  5. Business model canvas - Wikipedia

    en.wikipedia.org/wiki/Business_Model_Canvas

    The business model canvas is a strategic management template that is used for developing new business models and documenting existing ones. [2] [3] It offers a visual chart with elements describing a firm's or product's value proposition, [4] infrastructure, customers, and finances, [1] assisting businesses to align their activities by illustrating potential trade-offs.

  6. Power Pivot - Wikipedia

    en.wikipedia.org/wiki/Power_Pivot

    Power Pivot, formerly known as PowerPivot (without spacing), is a self-service business intelligence feature of Microsoft Excel which facilitates the creation of a tabular model to import, relate, and analyze data from a variety of sources.

  7. Statistical model validation - Wikipedia

    en.wikipedia.org/wiki/Statistical_model_validation

    Cross validation is a method of model validation that iteratively refits the model, each time leaving out just a small sample and comparing whether the samples left out are predicted by the model: there are many kinds of cross validation. Predictive simulation is used to compare simulated data to actual data.