Merge pull request #320 from Vhizux/feature/binomial-distribution

binomial distribution

mathgenerator/funcs/__init__.py

@@ -113,3 +113,4 @@ from .combine_like_terms import *
 from .signum_function import *
 from .conditional_probability import *
 from .arc_length import *
+from .binomial_distribution import *

mathgenerator/funcs/binomial_distribution.py

@@ -0,0 +1,42 @@
+from .__init__ import *
+
+
+def factorial(n):
+
+    if n == 1 or n == 0:
+        return 1
+    else:
+        return n * factorial(n - 1)
+
+
+def newton_symbol(n, k):
+    return factorial(n) / (factorial(k) * factorial(n - k))
+
+
+def binomialDistFunc():
+
+    rejected_fraction = float(random.randint(30, 40)) + random.random()
+    batch = random.randint(10, 20)
+    rejections = random.randint(1, 9)
+
+    answer = 0
+
+    rejected_fraction = round(rejected_fraction, 2)
+
+    problem = "A manufacturer of metal pistons finds that, on average, {0:}% "\
+        "of the pistons they manufacture are rejected because " \
+        "they are incorrectly sized. What is the probability that a "\
+        "batch of {1:} pistons will contain no more than {2:} " \
+        "rejected pistons?".format(rejected_fraction, batch, rejections)
+
+    for i in range(0, rejections + 1):
+        answer += newton_symbol(float(batch), float(i)) * ((rejected_fraction / 100.) ** float(i)) * \
+            ((1 - (rejected_fraction / 100.)) ** (float(batch) - float(i)))
+
+    answer = round(100 * answer, 2)
+
+    return problem, answer
+
+
+binomial_distribution = Generator("Binomial distribution", 107,
+                                  "P(X<x)=", "c", binomialDistFunc)