To solve this problem, we need to analyze the distribution pattern of the oyster larvae densities across different sites and days. Here's a detailed, step-by-step approach:
1. Tabulation of Densities:
Let's rewrite the given data clearly:
- Day 1: Site W - 40, Site X - 22, Site Y - 0, Site Z - 7
- Day 2: Site W - 3, Site X - 1, Site Y - 14, Site Z - 26
- Day 3: Site W - 2, Site X - 6, Site Y - 3, Site Z - 1
2. Flattening the Densities:
Combine all the densities into a single list to observe the spread across the days and sites:
```
all_densities = [40, 22, 0, 7, 3, 1, 14, 26, 2, 6, 3, 1]
```
3. Count Unique Densities:
Identify the unique values within these densities to understand diversity in the measurements:
```
unique_densities = {0, 1, 2, 3, 6, 7, 14, 22, 26, 40} # Total 10 unique densities
```
4. Determine the Distribution Pattern:
- Uniform Distribution: This would imply that there are no major variations in the density values and each site/day would have nearly identical densities. The unique count of densities and the varying values suggest it is not uniform.
- Stationary Distribution: This implies the density pattern remains unchanged over days. We see clear variations day-to-day, hence it isn't stationary.
- Random Distribution: If more than half the samples have zero or vary wildly without any apparent clustering. Since many sites show notable values and not exceeding half are zero, it isn't random.
- Clumped Distribution: This is characterized by several densities being grouped closely within certain regions or days. Given the sharp contrasts between certain site densities on the same days, this suggests a clumped distribution.
5. Conclusion:
Considering the detailed analysis above, we conclude that the distribution pattern of oyster larvae densities is:
```
D. clumped
```
Therefore, the oyster larvae exhibit a clumped distribution pattern.
