   # Square Analysis Of Chi Square Test

Pages: 4 (791 words) / Published: Dec 14th, 2015
3b. Chi squared analysis

A chi-square test is also referred to X². It is a statistical test that is used to find a significant difference between the observed data to the expected data in one or more groups. To calculate a chi square you have to carry out the equation, X^2= ∑▒(O-E)"²" ÷E.
Hₒ = this means that statistically there is no change between the observed and the expected frequencies of the results.
Hₐ = this means that there is a significant change between the observed and the expected frequencies of the results.
We used the chi square method on a corn cob. We started of using a punnet square to find all the phenotypes of the corn cob.

PS Ps pS ps
PS PPSS PPSs PpSS PpSs
Ps PPSs PPss PpSs Ppss pS PpSs PpSs ppSS ppSs ps PpSs Ppss ppSs ppss
This suggests to scientists that there is a significant difference between the table results and the critical value results suggesting that the hypothesis (which was that colour blindness isnt sex linked) is wrong as these results show differently.
We were able to find these figures by using this equation:
Expected cell frequency = row total x column total % n
We knew the observed results and the total amount of people asked (which was 1360)
Males expected cell frequency = (56+14) x (56+754) % 1360 = 42 (colour blind)
Females expected cell frequency = (56+14) x (14+536) % 1360 = 28 (colour blind)
Males expected cell frequency = (754+536) x (56+754) % 1360 = 768 (not colour blind)
Females expected cell frequency = (754+536) x (14+536) % 1360 = 522 (not colour