# Chi-squared test for continuous variables (averages)

I'm looking for a suitable statistical test for my situation. The best way I can think of describe it is a Chi-Squared test for continuous data. Please tell me otherwise.

Here is a made up scenario: Say we spend a few days observing whales and sharks in the Atlantic and Indian oceans. Here are the counts in a contingency table:

|          |Atlantic |Indian |Total |
|----------|---------|-------|------|
| whales   | 8       | 2     | 10   |
| sharks   | 1       | 5     | 6    |
|----------|---------|-------|------|
| Total:   | 9       | 7     | 16   |


Here I use the Chi-squared test to determine if the number of whales/sharks are independent to ocean location.

Lets say now I consider another metric: average weight of the animals. Here again is the table:

|          |Atlantic |Indian |Avg.  |
|----------|---------|-------|------|
| whales   | 6.9     | 7.2   | 7.1  |
| sharks   | 2.3     | 2.9   | 2.5  |
|----------|---------|-------|------|
| Avg.:    | 4.3     | 5.4   | 4.9  |


Instead of totals, I now have averages for the total of the populations along the side and last row. Here is my question: is the average weight of an animal independent to the ocean? Which test do I use now?

Just as a side note, the population sizes of each category might be very uneven such as a ratio of 1:999.

Side comment: What I find very interesting in the way you ask your question is that indeed there are striking similarities between a 2-way ANOVA and a $\chi^2$ test.