From 30941757057bbb592045751adbf82ac33eb092bc Mon Sep 17 00:00:00 2001
From: Dylan Stockard Problem 2.1
given credit. Pick one of the two.
Simulation procedure:
A. np.random.choice([0, 1], bus.shape[0])
A. np.random.choice([-1, 1], bus.shape[0])
B.
np.random.choice(bus['late'], bus.shape[0], replace = True)
C. Randomly permute the 'late'
column
Simulation procedure:
A. np.random.choice([0, 1], bus.shape[0])
A. np.random.choice([-1, 1], bus.shape[0])
B.
np.random.choice(bus['late'], bus.shape[0], replace = True)
C. Randomly permute the 'late'
column
Test statistic
A. Number of values below 1
A. Number of values below 0
B. np.mean
C. np.std
D. TVD
[0, 1]
for all
+we can simulate this by randomly generating [-1, 1]
for all
buses. This is what option A) does. Test statistic:
Since we know the number of buses, we can use the number of values below
-1 to determine whether we have more
+0 to determine whether we have more
early buses, more late buses, or the same amount. Similarly, the mean
-will give us a value between 0 and
-1, where 0.5 means we have the equal early and late
-buses, while 0 represents only early
+will give us a value between -1 and
+1, where 0 means we have the equal early and late
+buses, while -1 represents only early
buses, and 1 represents only late
buses.
@@ -381,7 +381,7 @@ 'line'
column?
Simulation procedure:
A. np.random.choice([0, 1], bus.shape[0])
A. np.random.choice([-1, 1], bus.shape[0])
B.
np.random.choice(bus['late'], bus.shape[0], replace = True)
C. Randomly permute the 'late'
column
'time'
column?
Simulation procedure:
A. np.random.choice([0, 1], bus.shape[0])
A. np.random.choice([-1, 1], bus.shape[0])
B.
np.random.choice(bus['late'], bus.shape[0], replace = True)
C. Randomly permute the 'late'
column