Mendelian Genetics

Long before anyone had seen a gene, Gregor Mendel worked out the rules of inheritance by counting pea plants. His central insight was to separate what an organism carries from what it shows: its genotype is the pair of alleles it inherits at a gene, while its phenotype is the trait those alleles produce. A dominant allele masks a recessive one, so two different genotypes — a homozygous dominant and a heterozygote — can display the exact same phenotype. Keeping these two layers distinct is the whole game: the visible trait never tells you the full genotype by itself.

From there, inheritance becomes probability. Each parent passes one allele per gene at random, so a cross is just a set of independent coin flips, and a Punnett square is the bookkeeping that turns those flips into offspring ratios — the classic 3:1 phenotype ratio, or 1:2:1 by genotype, from a monohybrid cross. But a real sample of offspring never lands exactly on the predicted numbers. To decide whether the deviation is just sampling noise or evidence that your model is wrong, you use the chi-square test for goodness of fit, comparing observed counts against what the cross predicts.

Topic 5.3 infographicAdd bio5.3.svg to /bio/ to display

The mistakes here cluster around those two layers. One is collapsing genotype into phenotype — reading a dominant trait as if it pinned down the genotype, or assuming "dominant" means "more common" (U5-BIO1, U5-BIO7). The others live in the counting: mishandling the probability of a cross or misreading a Punnett square (U5-BIO2, U5-BIO8), and treating chi-square as a yes/no verdict rather than a comparison of observed and expected counts against a threshold (U5-BIO9). Every scenario here asks you to reason from alleles to traits to predicted ratios, and to know when the data actually contradict the model.