In assessing data that fell into two phenotypic classes, a geneticist observed values of 250:150. She decided to perform a x² analysis by using the following two different null hypotheses: (a) the data fit a 3:1 ratio, and (b) the data fit a 1:1 ratio. Calculate the x² values for each hypothesis. What can be concluded about each hypothesis?

Key Concepts

Chi-Square Test (x² Analysis)

The Chi-Square test 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 observed phenotypic ratios fit a specific genetic hypothesis, such as Mendelian inheritance patterns. The test calculates a Chi-Square statistic, which is then compared to a critical value from the Chi-Square distribution to determine significance.

Null Hypothesis

A null hypothesis is a statement that there is no effect or no difference, serving as a starting point for statistical testing. In this context, the null hypotheses are that the observed data fit either a 3:1 ratio or a 1:1 ratio. By testing these hypotheses, the geneticist can determine if the observed phenotypic ratios are consistent with Mendelian inheritance or if other factors may be influencing the results.

Phenotypic Ratio

A phenotypic ratio is the relative frequency of different phenotypes observed in a population, often resulting from genetic inheritance patterns. In this case, the observed ratio of 250:150 can be analyzed against expected ratios, such as 3:1 or 1:1, to evaluate the genetic basis of the traits. Understanding these ratios is crucial for interpreting the results of the Chi-Square test and drawing conclusions about the underlying genetic mechanisms.