Table:
0
A
B
C
D
E
1
\theta_i
Simulated datasets (step 2)
Summary statistic \omega_{S,i} (step 3)
Distance \rho(\omega_{S,i}, \omega_E) (step 4)
Outcome (step 4)
2
0.08
AABAAAABAABAAABAAAAA
8
2
accepted
3
0.68
AABBABABAAABBABABBAB
13
7
rejected
4
0.87
BBBABBABBBBABABBBBBA
9
3
rejected
5
0.43
AABAAAAABBABBBBBBBBA
6
0
accepted
6
0.53
ABBBBBAABBABBABAABBB
9
3
rejected

Questions and formulas:
Question: What is the highest summary statistic of the algorithm with a distance larger than 2 and simulated datasets of aabbababaaabbababbab?
Formula: MAX(FILTER(C1, (D1>2)*(B1="aabbababaaabbababbab")))
Formula2: MAX(FILTER(C2:C6, (D2:D6>2)*(B2:B6="aabbababaaabbababbab")))
Level: easy
Question: What is the summary of the algorithm with a theta i of 0.43?
Formula: SUM(FILTER(C1, A1=0.43))
Formula2: SUM(FILTER(C2:C6, A2:A6=0.43))
Level: easy