Chi-square

Week 2: Wednesday, September 3rd; Week 4: Monday, September 15th: Monohybrids and Dihybrids; Chi; Pedigree

this analysis measures the amount that observed data differs from an expected outcome based on a proposed hypothesis

Chi-square (X²)

this hypothesis, which supports independent assortment, assumes there’s no significant difference between observed and expected results, so you accept it (fail to falsify).

null hypothesis (H₀)

this hypothesis, which supports gene linkage, assumes there is a significant difference between observed and expected results, so you reject H₀ (falsify)

alternative hypothesis (H₁)

true or false: Significance levels are set at p < 0.05 for acceptance of an outcome

false. Significance levels are set at p > 0.05 for acceptance of an outcome

true or false: a p value of ≤ 0.05 is deemed to extraordinary, thus falsifying a hypothesis (requires a hypothesis reformation)

true

_______ can be calculated as (the number of categories in the data set) - 1

degrees of freedom (dof)

_______ is what you actually see in the data set

observed number

dividing the lowest observed numbers by all the other numbers gives you the _______

observed ratio

multiplying the sum of the boserved number by each expected ratio as a fraction gives you the _______

expected number

corm kernels high in _______ content form a rounded, plump, smooth-looking kernel

starch

when sugar content increases, the higher sugar ratio causes greater dehydration of the endosperm layer, causing a _______ appearance.

wrinkled

true or false: the wrinkled appearance in corn kernels may also influence how the color of the kernel is perceived, often making it look darker

true

true or false: the coloration difference of corn kernels is a factor of pigment rather than sugar content

false. the coloration difference of corn kernels is a factor of sugar content rather than pigmentation