For a variety of reasons, the phenotypic ratios observed from real crosses rarely match the exact ratios expected based on a Punnett Square or other prediction techniques. There are many possible explanations for deviations from expected ratios. Sometimes these deviations are due to sampling effects, in other words, the random selection of a non-representative subset of individuals for observation. On the other hand, it may be because certain genotypes have a less than 100% survival rate. For example, Drosophila crosses sometimes give unexpected results because the more mutant alleles a zygote has the less likely it is to survive to become an adult. Genotypes that cause death for embryos or larvae are underrepresented when adult flies are counted.
The χTest For Goodness-of-fit
A statistical procedure called the chi-square (χ2) test can be used to help a geneticist decide whether the deviation between observed and expected ratios is due to sampling effects, or whether the difference is so large that some other explanation must be sought by re-examining the assumptions used to calculate the expected ratio. The procedure for performing a chi-square test is covered in the labs.