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diff --git a/q01_cond_prob/__pycache__/__init__.cpython-36.pyc b/q01_cond_prob/__pycache__/__init__.cpython-36.pyc
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diff --git a/q01_cond_prob/__pycache__/build.cpython-36.pyc b/q01_cond_prob/__pycache__/build.cpython-36.pyc
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diff --git a/q01_cond_prob/build.py b/q01_cond_prob/build.py
index 46a16ee..00afedd 100644
--- a/q01_cond_prob/build.py
+++ b/q01_cond_prob/build.py
@@ -1,3 +1,4 @@
+# %load q01_cond_prob/build.py
 # So that float division is by default in python 2.7
 from __future__ import division
 
@@ -7,6 +8,17 @@
 
 
 # Enter Code Here
+def cond_prob(df):
+    x=len(df[df.Neighborhood == 'OldTown'])
+    y=len(df)
+    return (x/y) * (x/(y-1)) * (x/(y-2))
 
 
 
+x=len(df[df.Neighborhood == 'OldTown'])
+y=len(df)
+(x/y) * (x/y) * (x/y)
+0.00045
+cond_prob(df)
+
+
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diff --git a/q02_confidence_interval/__pycache__/__init__.cpython-36.pyc b/q02_confidence_interval/__pycache__/__init__.cpython-36.pyc
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diff --git a/q02_confidence_interval/__pycache__/build.cpython-36.pyc b/q02_confidence_interval/__pycache__/build.cpython-36.pyc
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diff --git a/q02_confidence_interval/build.py b/q02_confidence_interval/build.py
index 023b81e..7bd409e 100644
--- a/q02_confidence_interval/build.py
+++ b/q02_confidence_interval/build.py
@@ -1,13 +1,30 @@
+# %load q02_confidence_interval/build.py
 # Default imports
 import math
 import scipy.stats as stats
 import pandas as pd
 import numpy as np
+
 df = pd.read_csv('data/house_pricing.csv')
 sample = df['GrLivArea']
 
 
 # Write your solution here :
+def confidence_interval(sample):
+    sample_mean = sample.mean()
+    sample_size=len(sample)
+    z_critical = stats.norm.ppf(q = 0.95)
+    pop_stdev = df['GrLivArea'].std()
+    margin_of_error = z_critical * (pop_stdev/math.sqrt(sample_size))
+
+    confidence_interval1 = (sample_mean - margin_of_error,
+                           sample_mean + margin_of_error) 
+    
+    return confidence_interval1
+
+
+
 
+confidence_interval(sample=sample)
 
 
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