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 ?
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.
Chi-Squared values and probabilities of goodness of fit of segregation ratios of F2 and backcross generations in a study of inheritance of leaf trichomes trait in three cross combinations are shown in Table 4.
The segregation ratios showed non-significant chi-squared values for the segregation ratios in F2 and backcross generations of the two crosses.
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.
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.
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.