Concepts - Part II

1. The binomial distribution provides the probability of a certain number of successful events out of n trials.
   
   
2. The Chi-square test is used to approximate the binomial distribution when we have discrete classes and the number of events is large (>30). Observed and expected numbers are used to calculate a Chi-square, not probabilities. Probabilities of each event are multiplied by the total number of events to determine the expected number of events for each class. Typically the degrees of freedom associated with a Chi-square test is one less than the total number of classes.
   
   
3. Type I error is the probability of rejecting the null hypothesis when it is in fact true.
   
   
4. Yate's correction for continuity is used for the contingency chi-square test.
   
   
5. The homogeneity Chi-square test is used to determine whether the data from different experiments (families) is homogeneous. Lack of homogeneity is evidence that the experiment is not repeatable or that one cross has a different segregation ratio than the other crosses.
   
   
6. The contingency chi-square can be used to evaluate whether there is evidence that two factors are independent and we have no prior knowledge of the expected ratios for each factor.
   
   
7. Meiosis - The diploid number of chromosomes is reduced to the haploid level. The random assortment of chromosomes along the metaphase plate results in different combinations of alleles in each gamete. Crossing over also results in new allelic combinations.
   
   
8. Genetic variability is created by independent assortment and by crossing over.
   
   
9. Map units are measured in cM between loci on a chromosome. Recombination frequency is the observed recombination between loci and does not consider 2-strand double crossovers. The observed recombination must be increased to account for unobserved 2-strand double crossovers.