How can a chi-squared test be applied to data from dihybrid crosses to determine significance?

The chi-squared test is a statistical method used to determine whether there is a significant difference between observed and expected frequencies in genetic data, particularly in dihybrid crosses. Here’s how the chi-squared test can be applied to analyze data from dihybrid crosses to assess significance:

Steps to Apply the Chi-Squared Test

1. Formulate Hypotheses:
   • Null Hypothesis (H0): Assumes that there is no significant difference between observed and expected frequencies, suggesting that the genes assort independently (i.e., they are unlinked).
   • Alternative Hypothesis (Ha): Assumes that there is a significant difference between observed and expected frequencies, suggesting that the genes are linked.
2. Collect Data:
   • Conduct a dihybrid cross and observe the phenotypes of the offspring. For example, if you cross two heterozygous plants (RrYy x RrYy), you might observe:
     • Round Yellow (RY): 78
     • Round Green (rY): 6
     • Wrinkled Yellow (Ry): 4
     • Wrinkled Green (ry): 12