chi-square distribution

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chi-square dis·tri·bu·tion

a variable is said to have a chi-square distribution with K degrees of freedom if it is distributed like the sum of the squares of K independent random variables, each of which has a normal (gaussian) distribution with mean zero and variance one. The chi-square distribution is the basis for many variations of the chi-square(d) test, perhaps the most widely used test for statistical significance in biology and medicine.
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References in periodicals archive ?
Factors Affecting Gastrointestinal Haemorrhage, Results of Chi-Squared Test
From the P - values in Chi-squared test, it can be interpreted that the factors associated with the occurrence of gastrointestinal haemorrhage are total leucocyte count more than 10,000/[mm.sup.3], PT-INR more than 1.5, amount of bilirubin more than 10 mg/dL and alkaline phosphatase level more than 150 IU.
The primary purpose of this book is to provide a detailed exploration of the theory, methods, and applications of the chi-squared goodness of fit test first advanced by Karl Pearson over 100 years ago.
For this set of data, you might use a chi-squared test to find out if these four groups are the same.
I also demonstrated the advantages of AOM over ANOVA and chi-squared. If want to have a better handle on a number of your statistics, take a minute and think of the dozens of applications
A comparison of some continuity corrections for the chi-squared test on 2 x 2 tables.
Contingency tables involving small numbers and the chi-squared test.
The main statistical technique used is chi-squared analysis, which permits the analyst to determine the significance of the deviations of a set of numbers from their expected values.
We present a simple new function, the cumulative chi-squared distribution, for assessing regions of misfit in a diffraction pattern and introduce a matrix which relates the impact of individual points in a powder diffraction pattern with improvements in the estimated standard deviation of refined parameters.
Further, Pleasants (1994) repeats an inaccuracy, first stated by Poole and Rathcke (1979), that the statistic P, when multiplied by n - 1, and divided by its expected value, is approximately distributed as chi-squared on n - 1 df.