diff --git a/week3/README.MD b/week3/README.MD
index 353d3867626168ea1b5c87f3bb855cbc39d9a296..2751a4d591520f4bed82012dca73424421220d7e 100644
--- a/week3/README.MD
+++ b/week3/README.MD
@@ -4,4 +4,4 @@
 
 Code is [here](random_walker.py).
 
-![](img/random_walker.jpg)
+![](random_walker.jpg)
diff --git a/week3/random_walker.py b/week3/random_walker.py
index 24e797b4c15a206497a1032adb3a7ce239da5828..c2f38fd50227f0c00b43f8d6b2c865c0c53f5ffa 100644
--- a/week3/random_walker.py
+++ b/week3/random_walker.py
@@ -22,7 +22,6 @@ def build_LFSR(seed, bits_needed=1000):
 walker_states = np.zeros((10, 1000))
 
 # create our seeds by grabbing a 16 bit number from the LSB of the current time in us
-# cheating and just adding a fixed delay to get different seeds
 seeds = []
 for i in range(10):
     delay = .1
@@ -41,7 +40,7 @@ timestep = np.array(range(1000))
 import matplotlib.pyplot as plt
 plt.plot(walker_states.T) # transpose it so we can plot it
 
-# for the 3 sigma lines, we will plot the sqrt of the timestep and divide the result by 1.5 to plot above and below the mean (0)
+# for the 3 sigma lines, we will multiply the sqrt of the timestep and divide the result by 1.5 to plot above and below the mean (0)
 plt.plot(timestep, 1.5 * np.sqrt(timestep), color='black', alpha = 0.25)
 plt.plot(timestep, -1.5 * np.sqrt(timestep), color='black', alpha = 0.25)
 plt.show()