Using publicly available code and data, we present a systematic study of projection biases in the weak lensing analysis of the first year of data from the Dark Energy Survey (DES) experiment. In the analysis we used a $Lambda$CDM model and three two-point correlation functions. We show that these biases are a consequence of projecting, or marginalizing, over parameters like $h_0$, $Omega_b$, $n_s$ and $Omega_ u$ that are both poorly constrained and correlated with the parameters of interest like $Omega_m$, $sigma_8$ and $S_8$. Covering the relevant parameter space we show that the projection biases are a function of where the true values of the poorly constrained parameters lie with respect to the parameter priors. For example, biases can exceed the 1.5$sigma$ level if the true values of $h$ and $n_s$ are close to the top of the priors range and the true values of $Omega_b$ and $Omega_ u$ are close to the bottom of the range of their priors. We also show that in some cases the 1D confidence intervals can be over-specified by as much as 30%. Finally we estimate these projection biases for the analysis of three and six years worth of DES data.
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