In statistics, a pivotal quantity or pivot is a function of observations and unobservable parameters such that the function's probability distribution does not depend on the unknown parameters (including nuisance parameters). A pivot quantity need not be a statistic—the function and its value can depend on the parameters of the model, but its distribution must not. If it is a statistic, then it is known as an ancillary statistic. More formally, let be a random sample from a distribution that depends on a parameter (or vector of parameters) . Let be a random variable whose distribution is the same for all . Then is called a pivotal quantity (or simply a pivot). Pivotal quantities are commonly used for normalization to allow data from different data sets to be compared. It is relatively easy to construct pivots for location and scale parameters: for the former we form differences so that location cancels, for the latter ratios so that scale cancels. Pivotal quantities are fundamental to the construction of test statistics, as they allow the statistic to not depend on parameters – for example, Student's t-statistic is for a normal distribution with unknown variance (and mean). They also provide one method of constructing confidence intervals, and the use of pivotal quantities improves performance of the bootstrap. In the form of ancillary statistics, they can be used to construct frequentist prediction intervals (predictive confidence intervals). (Wikipedia).
How to find the five number summary for a set of ODD numbers. Finding min, max, median, Q1 and Q3 in simple steps.
From playlist Basic Statistics (Descriptive Statistics)
Definition of critical numbers and two examples of how to find critical numbers for a polynomial and a rational function.
From playlist Calculus
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From playlist Prime Numbers, HCF and LCM - GCSE 9-1 Maths
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An introduction to prime numbers and the Fundamental Theorem of Arithmetic. Trial Division and the Sieve of Eratosthenes are also covered. Textbook: Rosen, Discrete Mathematics and Its Applications, 7e Playlist: https://www.youtube.com/playlist?list=PLl-gb0E4MII28GykmtuBXNUNoej-vY5Rz
From playlist Discrete Math I (Entire Course)
Excel Magic Trick 1398: DAX Formulas for Running Total and % of Running Total & other DAX Tricks
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From playlist Excel Running Total Calculations: PivotTables, Excel Formulas & DAX Formulas
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From playlist Dashboards: How To Build Them for Excel & Power BI Desktop . Playlist of Videos
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From playlist Pivot Tables
Excel Magic Trick 1396: PivotTable Show Values As: Running Total and % of Running Total (2 Examples)
Download Files: Start File: https://excelisfun.net/files/EMT1396-97.xlsx See how to: 1. (00:13) Introduction. What is a Running Total or Cumulative Frequency. What is a % Running Total 2. (03:10) Example 1: Grouping Integer Values for # of Transactions with a Quantity between an Lower
From playlist Excel Running Total Calculations: PivotTables, Excel Formulas & DAX Formulas
Excel Magic Trick 1336: Power Query: Import Big Data Text Files: Connection Only or Data Model?
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From playlist Excel Data Analysis Tricks
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From playlist Excel 2013 PowerPivot Playlist of Videos
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From playlist BUSINESS MATH - THE SIMPLEX METHOD
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Sign up for our Excel webinar, times added weekly: https://www.excelcampus.com/blueprint-registration/ Learn why the pivot table calculation type defaults to Count sometimes, and how to fix it to default to Sum. https://www.excelcampus.com/pivot-tables/calculation-default-to-sum/ One of
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All 9 files for video in this zipped folder: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/DataModeling/MSPTDA-23-DownloadAllFiles.zip Download file individually at class web site: https://people.highline.edu/mgirvin/AllClasses/348/MSPTDA/Content/DataModeling/DataModeli
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