# Chi Square Testing - binary outcome analysis

I have formed a contingency table for my binary outcome experiment that has been discussed in my previous question : binary outcome testing

One of my hypothesis says that females are better at identifying cars and I am trying to use chi-square testing.

So I get a table like this where I have summed up all predictions:

| Bike Predicted (actual 100) |     Car Predicted(actual 100)|
Male      |        50                   |             50               |
Female    |        40                   |             60               |

I have 2 questions regarding the above formulation.

1. Is there any way I can account for what the actual image was? I basically want the hypothesis to say that females are better at identify correct car images.

2. Using Chi-Square testing I can prove that the tyre prediction is independent/dependent of gender. However, if it is dependent, then can the actual number prove that females are better than males ? If not, can someone help me out on this !

• what about an odds ratio? – user20650 Mar 1 '13 at 0:10
• @user20650 can you tell me more about it ? – anon Mar 3 '13 at 18:20