

In [ ]:

    
%pylab
%matplotlib inline
import pandas as pd
from pandas import DataFrame, Series

import json
import seaborn as sns
import scipy

import IPython
from IPython.display import Image, display

pd.set_option('display.max_rows', 500)
pd.set_option('display.max_columns', 500)
pd.set_option('display.mpl_style', 'default') # Make the graphs a bit prettier

sns.set_style("darkgrid")
sns.set_palette("bright")

plt.rcParams['figure.figsize'] = (8, 6)
plt.rcParams['font.family'] = 'sans-serif'

import statsmodels.api as sm
import statsmodels.stats.api as sms
import statsmodels.formula.api as smf

Teaching Styles



In [ ]:

    
teachingdata = pd.read_table('../../DSUR/10/Teach.dat')
teachingdata.head(10)



In [ ]:

    
teachingdata.groupby("group").describe()



In [ ]:

    
sns.pointplot(data=teachingdata, x="group", y="exam", ci=68)

ANOVA



In [ ]:

    
g1 = teachingdata[teachingdata.group == 1].exam
g2 = teachingdata[teachingdata.group == 2].exam
g3 = teachingdata[teachingdata.group == 3].exam
f_value, p_value = scipy.stats.f_oneway(g1, g2, g3)
print "F(2,27) =", f_value, ", p =", p_value



In [ ]:

    
from pyvttbl import DataFrame
df=DataFrame()
df.read_tbl('../../DSUR/10/Teach.dat', 0, '\t')



In [ ]:

    
aov_pyvttbl = df.anova1way('exam', 'group')
print aov_pyvttbl



In [ ]: