Statistical Analysis: Chi Square AP Biology Ms. Haut

“Goodness of Fit Test” Chi Square (χ 2 ) Statistical analysis used to determine whether data obtained experimentally provides a “good fit” to the expected data Used to determine if any deviations from the expected results are due to random chance alone or to other circumstances

Chi Square (χ 2 ) Use the equation to test the “null” hypothesis –The prediction that data from the experiment will match the expected results χ 2 = Σ (observed results – expected results) 2 expected results When all else is equal, the value of χ 2 increases as the difference between the observed and expected values increase

Chi Square (χ 2 ) Once you have calculated the value of χ 2, you must determine the probability that the difference between the observed and expected values (χ 2 ) occurred simply by chance (sample error) You compare the calculated value to the appropriate value in a “degrees of freedom” table

Degrees of Freedom Degrees of freedom = # of categories – 1 Takes into account the natural increase in χ 2 as the number of categories increases dfP = 0.05P = 0.01P =

Scientists usually say that if their probability of getting the observed deviation from the expected results by chance is greater that 0.05 (5%), then we can accept the null hypothesis. –The differences we see between what we expected and what we actually see happened by chance sampling error If the probability is less than 0.05, then we reject the null hypothesis –The differences between expected and observed results did not just happen by chance sampling error

Practice A newly identified fruit fly mutant, cyclops eye (large and single in the middle of the head), is hypothesized to be autosomal dominant. The experimenter started with homozygous wild type females and homozygous cyclops males. The data from the F2 generation was 44 wild type males, 60 wild type females, 110 cyclops males and 150 cyclops females. Does this data support or reject the hypothesis? Use chi square to prove your position.

E = cyclops e = normal P = EE x ee F1 = all Ee F2 = Ee x Ee 3: cyclops:1 normal Expected:  Out of 364 offspring we should get an expected ratio of 273 cyclops: 91 normal What we actually got was 260 cyclops: 104 normal  2 =  ( ) (104-91) 2 91 = 169/ /91 = = 2.48

 2 = 2.48 Do we accept the hypothesis? Accept Reject Accepted: pattern of inheritance is autosomal dominant

Null Hypothesis: If the Mars Co. M & M sorters are doing their job correctly, then there should be no difference in M & M color ratios between actual store-bought bags of M &Ms and what the Mars Co. claims are the actual ratios.