systematically biased. For instance, students may collude and agree to grade each other generously. Even if there is no explicit collusion, there are studies which suggest that students grade each other generously (e.g. [@kpdjeb95]). To study this, we inflate or deflate the mean of the peer grades by a factor $r$. For instance, if $r=1.1$ then the mean peer mark is increased by 10%. On the other hand, if $r=0.9$ then the mean peer mark is decreased by 10%. We again use a binomial distribution of actual marks with a mean of 70.

![Performance of the generalised PeerRank method on marks coming from a binomial distribution with a mean of 70 (i.e. $p=0.7$) as we vary the bias in the peer marking. For $r>1$, peers return inflated marks. For $r<1$, peers return deflated marks. ](varerrorn1000p07)

In Figure 4, we plot the RMSE of the predicted grade again as a percentage of the 100 marks whilst we vary the bias in peer grades. For $0.75 \leq r \leq 1.25$, the error of the generalised PeerRank method is 5% or less of the total marks. That is, we are able to tolerate a bias of 25% in peer grades without significantly increasing 