diff --git a/__pycache__/__init__.cpython-36.pyc b/__pycache__/__init__.cpython-36.pyc index 2ba0c81..2d1121f 100644 Binary files a/__pycache__/__init__.cpython-36.pyc and b/__pycache__/__init__.cpython-36.pyc differ diff --git a/q01_cond_prob/__pycache__/__init__.cpython-36.pyc b/q01_cond_prob/__pycache__/__init__.cpython-36.pyc index a5c1ab2..65e91f5 100644 Binary files a/q01_cond_prob/__pycache__/__init__.cpython-36.pyc and b/q01_cond_prob/__pycache__/__init__.cpython-36.pyc differ diff --git a/q01_cond_prob/__pycache__/build.cpython-36.pyc b/q01_cond_prob/__pycache__/build.cpython-36.pyc index 4654504..cab3c06 100644 Binary files a/q01_cond_prob/__pycache__/build.cpython-36.pyc and b/q01_cond_prob/__pycache__/build.cpython-36.pyc differ diff --git a/q01_cond_prob/build.py b/q01_cond_prob/build.py index 46a16ee..7612fe4 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 @@ -5,8 +6,13 @@ df = pd.read_csv('data/house_pricing.csv') +def cond_prob(df): + A=df[df['Neighborhood']=='OldTown'].shape[0] + B=df.shape[0] + conditional_prob=(A/B)*((A-1)/(B-1))*((A-2)/(B-2)) + return conditional_prob + -# Enter Code Here diff --git a/q01_cond_prob/tests/__pycache__/__init__.cpython-36.pyc b/q01_cond_prob/tests/__pycache__/__init__.cpython-36.pyc index 9e8f52b..335d3b0 100644 Binary files a/q01_cond_prob/tests/__pycache__/__init__.cpython-36.pyc and b/q01_cond_prob/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q01_cond_prob/tests/__pycache__/test_q01_cond_prob.cpython-36.pyc b/q01_cond_prob/tests/__pycache__/test_q01_cond_prob.cpython-36.pyc index e8852e9..5465410 100644 Binary files a/q01_cond_prob/tests/__pycache__/test_q01_cond_prob.cpython-36.pyc and b/q01_cond_prob/tests/__pycache__/test_q01_cond_prob.cpython-36.pyc differ diff --git a/q02_confidence_interval/__pycache__/__init__.cpython-36.pyc b/q02_confidence_interval/__pycache__/__init__.cpython-36.pyc index 741ad2d..cf1b3ed 100644 Binary files a/q02_confidence_interval/__pycache__/__init__.cpython-36.pyc and b/q02_confidence_interval/__pycache__/__init__.cpython-36.pyc differ diff --git a/q02_confidence_interval/__pycache__/build.cpython-36.pyc b/q02_confidence_interval/__pycache__/build.cpython-36.pyc index b478df2..2f2fb6f 100644 Binary files a/q02_confidence_interval/__pycache__/build.cpython-36.pyc and b/q02_confidence_interval/__pycache__/build.cpython-36.pyc differ diff --git a/q02_confidence_interval/build.py b/q02_confidence_interval/build.py index 023b81e..d3b3e81 100644 --- a/q02_confidence_interval/build.py +++ b/q02_confidence_interval/build.py @@ -1,3 +1,4 @@ +# %load q02_confidence_interval/build.py # Default imports import math import scipy.stats as stats @@ -5,9 +6,15 @@ import numpy as np df = pd.read_csv('data/house_pricing.csv') sample = df['GrLivArea'] - - -# Write your solution here : - +def confidence_interval(sample=sample): + z_critical = stats.norm.ppf(q = 0.95) + sample_size=sample.size + sample_stdev = sample.std() + sample_mean=sample.mean() + margin_of_error = z_critical * (sample_stdev/math.sqrt(sample_size)) + Lower_confidence_interval = (sample_mean - margin_of_error) + Upper_confidence_interval = (sample_mean + margin_of_error) + return Lower_confidence_interval,Upper_confidence_interval +confidence_interval() diff --git a/q02_confidence_interval/tests/__pycache__/__init__.cpython-36.pyc b/q02_confidence_interval/tests/__pycache__/__init__.cpython-36.pyc index 2eb0cc4..ece1609 100644 Binary files a/q02_confidence_interval/tests/__pycache__/__init__.cpython-36.pyc and b/q02_confidence_interval/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q02_confidence_interval/tests/__pycache__/test_q02_confidence_interval.cpython-36.pyc b/q02_confidence_interval/tests/__pycache__/test_q02_confidence_interval.cpython-36.pyc index c3788ca..2f95d83 100644 Binary files a/q02_confidence_interval/tests/__pycache__/test_q02_confidence_interval.cpython-36.pyc and b/q02_confidence_interval/tests/__pycache__/test_q02_confidence_interval.cpython-36.pyc differ diff --git a/q03_t_test/__pycache__/__init__.cpython-36.pyc b/q03_t_test/__pycache__/__init__.cpython-36.pyc index cac7d29..9c3e456 100644 Binary files a/q03_t_test/__pycache__/__init__.cpython-36.pyc and b/q03_t_test/__pycache__/__init__.cpython-36.pyc differ diff --git a/q03_t_test/__pycache__/build.cpython-36.pyc b/q03_t_test/__pycache__/build.cpython-36.pyc index d55dfcf..1915f96 100644 Binary files a/q03_t_test/__pycache__/build.cpython-36.pyc and b/q03_t_test/__pycache__/build.cpython-36.pyc differ diff --git a/q03_t_test/build.py b/q03_t_test/build.py index f966b62..bd73743 100644 --- a/q03_t_test/build.py +++ b/q03_t_test/build.py @@ -1,9 +1,15 @@ +# %load q03_t_test/build.py # Default imports -import scipy.stats as stats +import scipy.stats as stat import pandas as pd df = pd.read_csv('data/house_pricing.csv') +def t_statistic(df): + df=df + t_stat,pvalue=stat.ttest_1samp(a=df[df['Neighborhood']=='OldTown']['GrLivArea'], popmean=df['GrLivArea'].mean()) + return pvalue,(t_stat>=0.10)#0.10 is the significance value for 90% + + -# Enter Code Here diff --git a/q03_t_test/tests/__pycache__/__init__.cpython-36.pyc b/q03_t_test/tests/__pycache__/__init__.cpython-36.pyc index c489290..fb968ae 100644 Binary files a/q03_t_test/tests/__pycache__/__init__.cpython-36.pyc and b/q03_t_test/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q03_t_test/tests/__pycache__/test_q03_t_test.cpython-36.pyc b/q03_t_test/tests/__pycache__/test_q03_t_test.cpython-36.pyc index ffd3551..e05f8cd 100644 Binary files a/q03_t_test/tests/__pycache__/test_q03_t_test.cpython-36.pyc and b/q03_t_test/tests/__pycache__/test_q03_t_test.cpython-36.pyc differ diff --git a/q04_chi2_test/__pycache__/__init__.cpython-36.pyc b/q04_chi2_test/__pycache__/__init__.cpython-36.pyc index 07afcf0..2fc805e 100644 Binary files a/q04_chi2_test/__pycache__/__init__.cpython-36.pyc and b/q04_chi2_test/__pycache__/__init__.cpython-36.pyc differ diff --git a/q04_chi2_test/__pycache__/build.cpython-36.pyc b/q04_chi2_test/__pycache__/build.cpython-36.pyc index 699bd6a..8f8bcd3 100644 Binary files a/q04_chi2_test/__pycache__/build.cpython-36.pyc and b/q04_chi2_test/__pycache__/build.cpython-36.pyc differ diff --git a/q04_chi2_test/build.py b/q04_chi2_test/build.py index 4f20455..c11ff96 100644 --- a/q04_chi2_test/build.py +++ b/q04_chi2_test/build.py @@ -1,10 +1,19 @@ +# %load q04_chi2_test/build.py # Default imports import scipy.stats as stats import pandas as pd df = pd.read_csv('data/house_pricing.csv') +def chi_square(df): + df=df + price = pd.qcut(df['SalePrice'], 3, labels = ['High', 'Medium', 'Low']) + freqtab=pd.crosstab(df['LandSlope'],price) + chi2,p_value,dof,expected=stats.chi2_contingency(freqtab) + test_result=(p_value<0.05) + return p_value,test_result + +chi_square(df) -# Enter Code Here diff --git a/q04_chi2_test/tests/__pycache__/__init__.cpython-36.pyc b/q04_chi2_test/tests/__pycache__/__init__.cpython-36.pyc index 45a1b92..573e9b4 100644 Binary files a/q04_chi2_test/tests/__pycache__/__init__.cpython-36.pyc and b/q04_chi2_test/tests/__pycache__/__init__.cpython-36.pyc differ diff --git a/q04_chi2_test/tests/__pycache__/test_q04_chi2_test.cpython-36.pyc b/q04_chi2_test/tests/__pycache__/test_q04_chi2_test.cpython-36.pyc index b2a8c04..289d6ea 100644 Binary files a/q04_chi2_test/tests/__pycache__/test_q04_chi2_test.cpython-36.pyc and b/q04_chi2_test/tests/__pycache__/test_q04_chi2_test.cpython-36.pyc differ