I have collected data regarding AI image generation. I generated 100 images from each tool and then listed down the number of images that were Male vs Female for different kinds of jobs.

                AI Tool 1            AI Tool 2           AI Tool 3
Job.            Female   Male        Female   Male       Female   Male

Arts            98       2           95       5          80       20
Engineering     2        98          30       70         10       90
Housekeeping    100      0           90       10         70       30

Now, my teacher has asked to do a Binomial test: comparing the gender ratio for each job generated by each tool with a hypothetical 1:1 ratio.

I have tried reading about the concept here:

https://www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/statistics/hypothesis-testing/hypothesis-testing-with-the-binomial-distribution.html

but I am not sure how exactly to implement it and which variables to use where. Since I have 3 different variables: gender, job type, and AI tool.

I have tried reading about the concept here:

https://www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/statistics/hypothesis-testing/hypothesis-testing-with-the-binomial-distribution.html

but I am not sure how exactly to implement it and which variables to use where. Since I have 3 different variables: gender, job type, and tool.

I have collected data on gender ratios that looks like this:

                Company A            Company B           Company C
Department      Female   Male        Female   Male       Female   Male
Arts            98       2           95       5          80       20
Engineering     2        98          30       70         10       90
Housekeeping    100      0           90       10         70       30

Now, my teacher has asked to do a Binomial test (followed by a Chi-square test) to determine whether the gender ratio is different from 1:1 to a statistically significant level. How can I do this in Python?

I have tried reading about the concept here:

https://www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/statistics/hypothesis-testing/hypothesis-testing-with-the-binomial-distribution.html

but I am not sure how exactly to implement it and which variables to use where. Since I have 3 different variables: gender, company name, and department. Or should I skip the departments and do a general ratio comparison between different companies?

I'm guessing there can be several different ways here so I am open to suggestions.

I have collected data regarding AI image generation. I generated 100 images from each tool and then listed down the number of images that were Male vs Female for different kinds of jobs.

                AI Tool 1            AI Tool 2           AI Tool 3
Job.            Female   Male        Female   Male       Female   Male 

Arts            98       2           95       5          80       20
Engineering     2        98          30       70         10       90
Housekeeping    100      0           90       10         70       30

Now, my teacher has asked to do a Binomial test: comparing the gender ratio for each job generated by each tool with a hypothetical 1:1 ratio.

I have tried reading about the concept here:

https://www.ncl.ac.uk/webtemplate/ask-assets/external/maths-resources/statistics/hypothesis-testing/hypothesis-testing-with-the-binomial-distribution.html

but I am not sure how exactly to implement it and which variables to use where. Since I have 3 different variables: gender, job type, and AI tool.