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oe(o-e) 2 /e Purple Smooth 9/16 = 56.25% 56.25% x total Purple Wrinkled 3/16 = 18.75% 18.75% x total Yellow Smooth 3/16 = 18.75% 18.75% x total Yellow.

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Presentation on theme: "oe(o-e) 2 /e Purple Smooth 9/16 = 56.25% 56.25% x total Purple Wrinkled 3/16 = 18.75% 18.75% x total Yellow Smooth 3/16 = 18.75% 18.75% x total Yellow."— Presentation transcript:

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4 oe(o-e) 2 /e Purple Smooth 9/16 = 56.25% 56.25% x total Purple Wrinkled 3/16 = 18.75% 18.75% x total Yellow Smooth 3/16 = 18.75% 18.75% x total Yellow Wrinkled 1/16 = 6.25% 6.25% x total

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6 Your ear of corn Expected: use Punnet Square data Observed #s are what you counted Parents both PpSs – Any deviations from data are due to chance and chance only H0 = No difference between expected and observed values; if so, they are due to CHANCE! If X2 > CV = REJECT H0 so other forces at work; not chance; different parents – P < or = to 5% If X2 < CV = ACCEPT H0 so deviation from data due to chance; no significant difference; in favor of 9:3:3:1 ratio – P > 5% so our data fits ratios… The lower the probability, the less safe we are in accepting that the difference is due to chance alone so we reject the null

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8 1) A large ear of corn has a total of 433 grains: including 271 purple & starchy, 73 purple & sweet, 63 yellow & starchy, and 26 yellow & sweet. We think: This ear of corn was produced by a dihybrid cross (PpSs x PpSs) involving two pairs of heterozygous genes resulting in a theoretical (expected) ratio of 9:3:3:1. X 2 = 8.04 so reject null Differences due to outside forces

9 2) In a certain reptile, eyes can be either black or yellow. Two black eyed lizards are crossed, and the result is 72 black eyed lizards, and 28 yellow-eyed lizards. We think: The black eyed parents were Bb x Bb. X 2 =.48 accept null In favor of ratio Differences due to chance

10 3) A sample of mice (all from the same parents) shows 58 Black hair, black eyes. 16 Black hair, red eyes, 19 White hair, black eyes, 7 White hair, red eyes X 2 =.53 accept null In favor of ratio Differences due to chance

11 How do you know? 4) A scientist wants to sample a population of birds for the ratio of males to females. It is generally expected that these birds will exist in a ratio of 50:50. How do you know? ~ ~In other words, if you collected one hundred of these birds 50 would be male and 50 would be female. However, when the scientist actually collects 100 of the birds he collects 45 males and 55 females. This issue raises the following important questions: Are the observed values close enough to the expected values to be scientifically accepted? Are the observed values close enough to the expected values to be scientifically accepted? Were the scientist’s observed values due to chance occurrence or is there actually a difference in the gender ratio of this bird? Were the scientist’s observed values due to chance occurrence or is there actually a difference in the gender ratio of this bird? Make a Punnet square of XX vs. XY Close enough Accept null so differences between observed & expected due to chance… Chi Square value:.10 < CV w/ df of 1

12 5) Mendel's data from one experiment with corn resulted in 5,474 smooth seeds (S_) and 1,850 wrinkled seeds (ss). Were the parents both heterozygous smooth? What ratio would you expect?


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