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If the set is a sample from the whole population, then the unbiased sample variance can be calculated as 1017.538 that is the sum of the squared deviations about the mean of the sample, divided by 11 instead of 12. A function VAR.S in Microsoft Excel gives the unbiased sample variance while VAR.P is for population variance.
When a member of the exponential family has been specified, the variance function can easily be derived. [4]: 29 The general form of the variance function is presented under the exponential family context, as well as specific forms for Normal, Bernoulli, Poisson, and Gamma. In addition, we describe the applications and use of variance functions ...
Algorithms for calculating variance play a major role in computational statistics.A key difficulty in the design of good algorithms for this problem is that formulas for the variance may involve sums of squares, which can lead to numerical instability as well as to arithmetic overflow when dealing with large values.
Variance (the square of the standard deviation) – location-invariant but not linear in scale. Variance-to-mean ratio – mostly used for count data when the term coefficient of dispersion is used and when this ratio is dimensionless, as count data are themselves dimensionless, not otherwise. Some measures of dispersion have specialized purposes.
A backup of an Excel Spreadsheet Add-in (DLL) .xll: Adds custom functionality; written in C++/C, Fortran, etc. and compiled into a special dynamic-link library: Macro .xlm: A macro is created by the user or pre-installed with Excel. Template .xlt: A pre-formatted spreadsheet created by the user or by Microsoft Excel. Module .xlv
Whether you use Microsoft Office Excel, Google Sheets or Apple Numbers, there’s a free spreadsheet for you. These budgeting templates will give you a head start from simple monthly and yearly ...
For any index, the closer to uniform the distribution, the larger the variance, and the larger the differences in frequencies across categories, the smaller the variance. Indices of qualitative variation are then analogous to information entropy, which is minimized when all cases belong to a single category and maximized in a uniform ...
Non-constant variance: in the simplest cases, weighted least squares might be used. Non-normal distribution for errors: in the simplest cases, a generalized linear model might be applicable. Unit root : taking first (or occasionally second) differences of the data, with the level of differencing being identified through various unit root tests.