Which of the following statements about computing statistically significant motifs is True? Every directed network will have at least one type of 3-node network motif O The directed configuration model can generate random directed networks preserving the in-degree and out-degree of each node The method we discussed in the lecture uses random sampling without replacement Suppose that m(G) is the number of "mutual out" instances in the given graph G, and m(G_r) is the random variable that counts the number of "mutual out" instances in a random graph.lf the probability that m(G_r) is larger than m(G) is 99%, the "mutual in" motif is more common in G than expected by chance with a 99% statistical confidence
Which of the following statements about computing statistically significant motifs is True? Every directed network will have at least one type of 3-node network motif O The directed configuration model can generate random directed networks preserving the in-degree and out-degree of each node The method we discussed in the lecture uses random sampling without replacement Suppose that m(G) is the number of "mutual out" instances in the given graph G, and m(G_r) is the random variable that counts the number of "mutual out" instances in a random graph.lf the probability that m(G_r) is larger than m(G) is 99%, the "mutual in" motif is more common in G than expected by chance with a 99% statistical confidence
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Transcribed Image Text:Which of the following statements about computing statistically significant
motifs is True?
Every directed network will have at least one type of 3-node network motif
The directed configuration model can generate random directed networks
preserving the in-degree and out-degree of each node
O The method we discussed in the lecture uses random sampling without
replacement
Suppose that m(G) is the number of "mutual out" instances in the given graph G,
and m(G_r) is the random variable that counts the number of "mutual out"
instances in a random graph.lf the probability that m(G_r) is larger than m(G) is
99%, the "mutual in" motif is more common in G than expected by chance with a
99% statistical confidence
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