On the minimum expected quantity for the validity of the chi-squared test in 2 * 2 tables

2 * 2 contingency table can often be analysed in an exact fashion by using Fisherʹs exact test and in an approximate fashion by using the chi-squared test with Yatesʹ continuity correction, and it is traditionally held that the approximation is valid when the minimum expected quantity E is ES5. Unfortunately, little research has been carried out into this belief, other than that it is necessary to establish a bound E>E*, that the condition ES5 may not be the most appropriate (Martin Andrés et al., 1992) and that E* is not a constant, but usually increasing with the growth of the sample size (Martin Andrés & Herranz Tejedor, 1997). In this paper, the authors conduct a theoretical experimental study from which they ascertain that E* value (which is very variable and frequently quite a lot greater than 5) is strongly related to the magnitude of the skewness of the underlying hypergeometric distribution, and that bounding the skewness is equivalent to bounding E (which is the best control procedure). The study enables estimating the expression for the above-mentioned E* (which in turn depends on the number of tails in the test, the alpha error used, the total sample size, and the minimum marginal imbalance) to be estimated. Also the authors show that E* increases generally with the sample size and with the marginal imbalance, although it does reach a maximum. Some general and very conservative validity conditions are ES35.53 (one-tailed test) and ES7.45 (two-tailed test) for alpha nominal errors in 1%hfh10%. The traditional condition ES5 is only valid when the samples are small and one of the marginals is very balanced; alternatively, the condition ES5.5 is valid for small samples or a very balanced marginal. Finally, it is proved that the chi-squared test is always valid in tables where both marginals are balanced, and that the maximum skewness permitted is related to the maximum value of the bound E*, to its value for tables with at least one balanced marginal and to the minimum value that those marginals must have (in non-balanced tables) for the chi-squared test to be valid