Hi, Can you help me with this question

A researcher sought advice about the growth rates of insects. Two species were collected from two locations and the counts of the three {3) different sexes were counted. The data structure used for modeling was: 'data.frame': I 11 obs. of 4 variables: 5 Sex Factor HI 3 levels \"EH","F","M\": 1 2 3 1 2 3 1 2 3 2 3 | 1 Location: I Factor w! 2 levels \"En","Ts": 1 1 1 2 2 2 1 1 1 2 2 3 Species : I Factor wf 2 levels \"g","Ht": 1 1 1 l 1 1 2 2 2 2 2 3 Count I int 9 12 51 2 E 22 4 29 12 5 B And the outcome of fitting all possible loglinear models [using the three factors in the order given above) was: I Model I of I Deviance ---| ----------- |--| --------- 1 | [1][2][3] | 3 | 33.313315 2 | [l][23] | 5 | 32.353132 3 | [13][2] | 4 | 5.335231 4 | [12][3] | 4 | 33.313211 5 | [12][23] | 3 | 33.235535 3 | [13][23] | 3 | 5.125353 2 | [12][13] | 2 | 3.334422 3 | [12][13][23]| 1 | 2.952334 3 | [123] | 3 | 3.333333 1. which model is the best one to explain the interrelationships among the three factors? Justify your selection. 2. hs a result of your model selection, would you have any concerns about the sampled insects being used as the experimental units in the analysis of their growth rates? Justify your answer. 3. what would the difference between models 6 and B be testing? 4. Which pairs of modelEs} test the interaction of location and species? 5. Explain the major flaw with this data set and the above analysis. what immediate recommendation(s} would you have to get the analysis done properly