For analyzing your simple animal behavior data, you can use the chi-square test or Fisher's exact test, depending on the specifics of your data. These tests are commonly used for analyzing categorical data, which seems to be the case with your observations of behavior categories

(e.g., walking, resting, feeding, nasal secretion).

The chi-square test can be used when you have two or more categorical variables and you want to determine if there is a significant association between them. In your case, you can examine if the behavior categories (walking, resting, feeding, nasal secretion) are influenced by the winter season. The chi-square test will help you determine if there is a significant relationship between the behavior categories and the winter season.

On the other hand, if you have a small sample size or some of the expected cell frequencies are low (less than 5), Fisher's exact test is a suitable alternative. This test is also used to determine if there is a significant association between categorical variables but is particularly useful when the sample size is small.

Before performing any statistical test, it is important to organize your data into a contingency table, where you can cross-tabulate the behavior categories with the winter season (e.g., columns represent behavior categories, rows represent the winter season, and the cells contain the observed frequencies). Once you have your contingency table, you can apply the appropriate statistical test to determine if there is a significant association between the behavior categories and the winter season.

Keep in mind that this is a general recommendation based on the information provided. Depending on the specific nature of your data and research question, other statistical tests may also be applicable. It is always best to consult with a statistician or a domain expert to ensure you select the most appropriate test for your analysis.

Yasiru Tishan@ thanks