Question 1
Two equally sized patches of the night sky are examined:
- Patch A contains $100$ stars
- Patch B contains $110$ stars
Is there a significant difference between these two patches of night sky? i.e., is one patch likely to contain a star cluster?
Question 2
Traffic to a site is examined in two time frames of equal duration
in time frame 1 (e.g., summer/June/morning), there were 100 visitors
in time frame 2 (e.g., winter/December/evening), there were 110 visitors
Is there a significant difference in site volume between these two time frames? i.e., is demand to the site governed by temporal factors?
Background
I would like to know if there is a statistical test designed to examine whether there is a significant difference between two groups. The values I am evaluating are aggregated counts (so is not a continuous measure or ordinal).
Since the values are aggregated counts, my first instinct was using the Chi-square test of independence. However, I can only find examples where a dichotomy is involved, resulting in a YES/NO, 1-0, TRUE/FALSE contingency table. But in my case, I cannot see an obvious way of representing my data in this dichotomous fashion.
I don't know how to explain this, but is there something like an A/B test, but with only a single row or a single column?