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Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
1983, Lotus 1-2-3 for MS-DOS, the first killer application for the IBM PC, it took the market from Visicalc in the early 1980s. 1983, Dynacalc for OS-9 a Unix-like operating system, similar to VisiCalc. [11] 1984, Lotus Symphony for MS-DOS, the follow-on to Lotus 1-2-3; 1985, Boeing Calc for MVS and MS-DOS, written by subsidiary of aviation ...
As it approaches zero there is less of a relationship (closer to uncorrelated). The closer the coefficient is to either −1 or 1, the stronger the correlation between the variables. If the variables are independent, Pearson's correlation coefficient is 0. However, because the correlation coefficient detects only linear dependencies between two ...
[1] [2] [3] Spreadsheets were developed as computerized analogs of paper accounting worksheets. [4] The program operates on data entered in cells of a table. Each cell may contain either numeric or text data, or the results of formulas that automatically calculate and display a value based on the contents of other cells.
In statistics, an effect size is a value measuring the strength of the relationship between two variables in a population, or a sample-based estimate of that quantity. It can refer to the value of a statistic calculated from a sample of data, the value of one parameter for a hypothetical population, or to the equation that operationalizes how statistics or parameters lead to the effect size ...
A perfectly monotonic increasing relationship implies that for any two pairs of data values X i, Y i and X j, Y j, that X i − X j and Y i − Y j always have the same sign. A perfectly monotonic decreasing relationship implies that these differences always have opposite signs. The Spearman correlation coefficient is often described as being ...
An odds ratio (OR) is a statistic that quantifies the strength of the association between two events, A and B. The odds ratio is defined as the ratio of the odds of event A taking place in the presence of B, and the odds of A in the absence of B. Due to symmetry, odds ratio reciprocally calculates the ratio of the odds of B occurring in the presence of A, and the odds of B in the absence of A.
Contrary to Tau-b, Tau-c can be equal to +1 or -1 for non-square (i.e. rectangular) contingency tables, [15] [16] i.e. when the underlying scale of both variables have different number of possible values. For instance, if the variable X has a continuous uniform distribution between 0 and 100 and Y is a dichotomous variable equal to 1 if X ≥ ...