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.

chi-square distribution

in statistical terms this is said of a variable 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 distribution with mean zero and variance of 1.
References in periodicals archive ?
I also demonstrated the advantages of AOM over ANOVA and chi-squared.
Some aspects of Verheij's use of chi-squared suggest the latter approach.
A fundamental assumption of the chi-squared test is that the cases one is studying are independent of one another.
The estimate one gives for the significance of a set of variations depends not only on the magnitude of those variations, but also on the degrees of freedom of the problem, and for this reason each chi-squared analysis should specify the degrees of freedom used.
This can be achieved by plotting the cumulative chi-squared function which is the weighted sum of the squares of the difference between observed and calculated powder diffraction patterns up to that point in the diffraction pattern.
The cumulative chi-squared plot clearly highlights the problems in fitting the cimetidine data and provides pointers to improving the fit to the data and hence obtaining an improved more accurate structural model.
A further indication of the importance of using a variable counting time scheme can be seen from the analysis of the cumulative chi-squared distribution for the refinement of the structure of famotidine (Figure 4).
Because all variables were presented as frequencies, statistical analysis was performed in accordance with the chi-squared ([chi square]) test to determine if the actual and expected values were similar by chance.