BIOL 202 Lecture Notes - Lecture 9: Random Number Table, Quadrat
1. Data Table: Abundance of red dots/species for clumped pattern using random coordinates
with the help of a random number table.
5 small
20 small
5 large
20 large
1
0
0
4
0
2
0
0
0
0
3
4
0
0
2
4
3
0
0
0
5
0
1
0
2
6
1
4
7
0
4
8
0
0
9
0
0
10
2
0
11
0
4
12
0
0
13
0
1
14
0
2
15
2
4
16
0
1
17
0
0
18
0
0
19
0
1
20
0
0
Average
1.4
0.3
8.8
1.25
Density
0.056
0.003
0.032
0.0125
% Error
266
80.39
109.2
18.30
2. Predicted ranking:1(best) – 4 (worst)
My predicted ranking would be 20 large at number one, 20 small at number two, 5 large at
number three, and then 5 small at number four, being the least accurate. My prediction is
based on the idea that variation increases as sample size increases, which leads to precision;
therefore, 20 large being the largest sample size and quadrat number would give the highest
variability.
3. Observed ranking: Based on table 1: 20 large gave us the most accurate estimate because it’s
percent error is the lowest, which is 18.30% followed by 20 small with percent error at
80.39%, then 5 large at 109.2% and 5 small with the highest percent error at 266% which
also makes it the least accurate way of getting estimates and thus the weakest sampling
design.
AFTER DATA ANALYSIS QUESTIONS:
1. Did we generally get more accurate estimates of density using larger quadrats?
Yes, we got more accurate estimates of density using larger quadrats because the average
percent error for large sample was 42.00% and for the small, 74.47%. this shows that large
samples got a smaller % error and thus more accurate answers.
find more resources at oneclass.com
find more resources at oneclass.com
Document Summary
Data table: abundance of red dots/species for clumped pattern using random coordinates with the help of a random number table. My predicted ranking would be 20 large at number one, 20 small at number two, 5 large at number three, and then 5 small at number four, being the least accurate. 80. 39%, then 5 large at 109. 2% and 5 small with the highest percent error at 266% which also makes it the least accurate way of getting estimates and thus the weakest sampling design. Randomly dispersed individuals gave better estimates because their percent error is lower than clumped. Try plotting number off verses total area sampled for both the large and small quadrats. This sampling would work best, if the distribution is clumped. For random distribution and uniform distribution, either of the two options would be good because 20 small and 5 large cover the same area i. e. 500 cm2.
