Monday’s Lab: M&M Genetics 1) Title/Date 2) Pre-lab (use sheets from today) –A) Key concepts & Equations –B) Materials List 3) Purposes (2-3) 4/5) STAPLE BOTH HANDOUTS IN LAB NOTEBOOK (100% complete) 6) Conclusion
Chi-square (Χ 2 ) Statistical Analysis -Used to determine if observed data are close enough to expected data Example P: Gg x Ggexpect 3:1 G = green g = albino Table ggAlbino 72GG or GgGreen (o – e)Expected# ObservedGenotypePhenotype Total = There is a small difference between observed & expected. Is it close enough to say this is a 3:1 or is there too much variance???? We use the Chi-square test to determine this.
Chi-square (Χ 2 ) - Used to determine if the observed data fall within acceptable limits & tests the validity of a null hypothesis - Null hypothesis – states there is NO statistically significant difference between the observed & expected values Χ 2 = Σ (o – e) 2 e o = observed e = expected Σ = sum of values
Phenotypeobserved (o)expected (e)(o – e)(o – e) 2 e Green White Table 7.4 Χ 2 = Σ (o – e) 2 e =
Phenotypeobserved (o)expected (e)(o – e)(o – e) 2 e Green White Table 7.4 Χ 2 = Σ (o – e) 2 e = 5.15 We now compare our calculated Χ 2 value with the Critical Values Table Remember: null hypothesis says there is NO significant difference between the observed & expected data.
Critical Values of the Chi-Square Distribution Probability (p) Degrees of Freedom (df) df = categories – 1categories = phenotypes = 2 – 1 df = 1 2. p value p = 0.05 for science 3. Compare calculated Χ 2 to table 5.15 > 3.84 REJECT null hypothesis…..observed data are not the same as expected Observed data are not a 3:1 ratio