I have the following human population data with me (based on a census) -
Number of women in each educational level (like Illiterate, literate but less than primary, high school, graduate). For the time being call then Educational level $1,2,3$ and so on. And corresponding to each educational level those women were categorized in different age groups (like $20-24$ years, $25-29$ years and so on). And then I have the parity numbers for women in each age group and correspondingly each educational level. So, in short if you pick a random women from the population data, you will have access to the age group and education level to which she belongs and her parity number.
Now, I want to understand the relationship between the mean parities (of women in all age groups) for women in two different educational level. So, I calculate average parities and construct a table with two columns - Women with education level $0$ and women with education level $1$. And I have age groups as my rows.
Now I am thinking of performing a paired t-test for these two columns to asses the relationship between means of these two categories(variables) but I am not sure if this is the appropriate test to perform. As I think these two columns are independent to each other which violates one of the assumptions of paired t-test. I have different sets of women under observation here instead of having same women for these two educational level. But this is simply not possible. Am I right or wrong here? Should I go with this test or should try other test (if yes then please tell me about those tests)?
Also, if anyone can suggest a better question (than testing the mean between these two levels of education) that can be framed from this data, that would also be kind of you.
P.S. - I am not sure if I have explained my data properly but in case of any confusion please let me know.