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Given a function that accepts an array, a range query (,) on an array = [,..,] takes two indices and and returns the result of when applied to the subarray [, …,].For example, for a function that returns the sum of all values in an array, the range query (,) returns the sum of all values in the range [,].
Functions of a single variable (such as sine and cosine) may be implemented by a simple array. Functions involving two or more variables require multidimensional array indexing techniques. The latter case may thus employ a two-dimensional array of power[x][y] to replace a function to calculate x y for a limited range of x and y values ...
In descriptive statistics, the range of a set of data is size of the narrowest interval which contains all the data. It is calculated as the difference between the largest and smallest values (also known as the sample maximum and minimum). [1] It is expressed in the same units as the data. The range provides an indication of statistical ...
Mathematica, [3] Matlab, [4] R [5] and GNU Octave [6] programming languages support all nine sample quantile methods. SAS includes five sample quantile methods, SciPy [ 7 ] and Maple [ 8 ] both include eight, EViews [ 9 ] and Julia [ 10 ] include the six piecewise linear functions, Stata [ 11 ] includes two, Python [ 12 ] includes two, and ...
In linear algebra, the column space (also called the range or image) of a matrix A is the span (set of all possible linear combinations) of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation. Let be a field.
MATLAB code given. 1,224 Text Classification 2008 [263] [264] U. Hoffman et al. Heart Disease Data Set Attributed of patients with and without heart disease. 75 attributes given for each patient with some missing values. 303 Text Classification 1988 [265] [266] A. Janosi et al. Breast Cancer Wisconsin (Diagnostic) Dataset
The five-number summary is a set of descriptive statistics that provides information about a dataset. It consists of the five most important sample percentiles: the sample minimum (smallest observation) the lower quartile or first quartile; the median (the middle value) the upper quartile or third quartile
To apply a Q test for bad data, arrange the data in order of increasing values and calculate Q as defined: Q = gap range {\displaystyle Q={\frac {\text{gap}}{\text{range}}}} Where gap is the absolute difference between the outlier in question and the closest number to it.