diff --git a/TurTLE/DNS_statistics.py b/TurTLE/DNS_statistics.py
index b0f3aeb3e27544c32f98feed64c4af09bd2016ad..d4a764f366cb5893589f4df7c5957a445312900b 100644
--- a/TurTLE/DNS_statistics.py
+++ b/TurTLE/DNS_statistics.py
@@ -34,12 +34,12 @@ def compute_statistics(
         strict_Parseval_check = True):
     """Run basic postprocessing on raw data.
     The energy spectrum :math:`E(t, k)` and the enstrophy spectrum
-    :math:`\\frac{1}{2}\omega^2(t, k)` are computed from the
+    :math:`\\frac{1}{2}\\omega^2(t, k)` are computed from the
 
     .. math::
 
         \sum_{k \\leq \\|\\mathbf{k}\\| \\leq k+dk}\\hat{u_i} \\hat{u_j}^*, \\hskip .5cm
-        \sum_{k \\leq \\|\\mathbf{k}\\| \\leq k+dk}\\hat{\omega_i} \\hat{\\omega_j}^*
+        \sum_{k \\leq \\|\\mathbf{k}\\| \\leq k+dk}\\hat{\\omega_i} \\hat{\\omega_j}^*
 
     tensors, and the enstrophy spectrum is also used to
     compute the dissipation :math:`\\varepsilon(t)`.
@@ -202,7 +202,7 @@ def compute_time_averages(self):
     .. math::
 
         U_{\\textrm{int}}(t) = \\sqrt{\\frac{2E(t)}{3}}, \\hskip .5cm
-        L_{\\textrm{int}} = \\frac{\pi}{2U_{int}^2} \\int \\frac{dk}{k} E(k), \\hskip .5cm
+        L_{\\textrm{int}} = \\frac{\\pi}{2U_{int}^2} \\int \\frac{dk}{k} E(k), \\hskip .5cm
         T_{\\textrm{int}} =
         \\frac{L_{\\textrm{int}}}{U_{\\textrm{int}}}
 
@@ -469,10 +469,10 @@ def plot_basic_stats(
         print('WARNING: CFL computation does not make sense for non-isotropic grids')
     a.plot(self.statistics['t'] / self.statistics['Tint'],
            sresolution,
-           label = '$(k_M \eta_K)^{-1}$ (spatial resolution)')
+           label = '$(k_M \\eta_K)^{-1}$ (spatial resolution)')
     a.plot(self.statistics['t'] / self.statistics['Tint'],
            tresolution,
-           label = '$\\frac{\\Delta t}{\\Delta x} \sqrt{3}\\| u \\|_\infty$ (CFL upper bound)')
+           label = '$\\frac{\\Delta t}{\\Delta x} \\sqrt{3}\\| u \\|_\infty$ (CFL upper bound)')
     a.set_ylim(top = 1.05*max(sresolution.max(),
                               tresolution.max()),
                               bottom = 0)