Zach D. answered • 07/01/21
STEM tutor specializing in math, chemistry, biology
The Chi-square test is a statistical test that evaluates the validity of a null hypothesis which states that there is no statistically significant difference between an expected and observed value, that is, that any variation from the expected value is due to chance alone, and not due to any external factors.
In genetics, the Chi-square test is used to determine whether disparities in allelic distribution in a population are due to chance alone, or some external factor (most likely environmental) that would result in a statistically significant difference in the expected allele probabilities and observed ones. There is a parameter in Chi-square analysis called the P-value (it is usually stated in the problem or given in a table along with the degrees of freedom).
The Chi-square formula is given as Χ2 = (o - e)2/ e (for one value, or the sum of individual factors of (o - e)2/e for non-individual values), where o is the observed value and e is the expected value. If this value is less than the P-value, then the null hypothesis is accepted and it can be determined that the variance is due to chance alone. If the Chi-square value exceeds the P-value, then the null hypothesis is rejected and it can be determined that the variance is due to more than chance, and there must be an external factor causing the variance.
*Note: The observed values are given by the phenotypic results of a cross, whereas the expected values are determined by Punnett Squares, which are statistically ideal probabilities*
