T. H. Morgan's data on eye color and wing form, shown in Figures 5.3 and 5.5, reveal genetic linkage between the two genes. Test this genetic linkage data with chi-square analysis, and show that the results are significantly different from the expectation under the assumption of independent assortment.

Verified step by step guidance

1. Identify the observed (O) and expected (E) values for each phenotype from the table.
2. Calculate the chi-square value for each phenotype using the formula: \( \chi^2 = \sum \frac{(O - E)^2}{E} \).
3. Sum the chi-square values for all phenotypes to get the total chi-square value.
4. Determine the degrees of freedom, which is the number of phenotypic categories minus 1.
5. Compare the total chi-square value to the critical value from the chi-square distribution table at the desired significance level to determine if the results are significantly different from the expectation under independent assortment.

Key Concepts

Genetic Linkage

Genetic linkage refers to the tendency of genes located close to each other on a chromosome to be inherited together during meiosis. This phenomenon contrasts with independent assortment, where genes segregate independently. T.H. Morgan's experiments demonstrated that certain traits, such as eye color and wing form in fruit flies, are linked, indicating that they are located on the same chromosome.

Chi-Square Analysis

Chi-square analysis is a statistical method used to determine if there is a significant difference between observed and expected frequencies in categorical data. In genetics, it helps assess whether the inheritance patterns of traits deviate from what would be expected under the assumption of independent assortment. A significant chi-square result suggests that the traits may be linked rather than assorting independently.

Observed vs. Expected Counts

In the context of genetic experiments, observed counts (O) are the actual data collected from experiments, while expected counts (E) are the theoretical values predicted based on a specific hypothesis, such as independent assortment. Comparing these counts using chi-square analysis allows researchers to evaluate the validity of their assumptions about genetic inheritance and linkage.