+
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+
+
+In [3]:
+
+
+
+
+
+
+import pandas
+chicks = pandas.read_csv("chickwts.txt")
+import plotnine
+from plotnine import *
+p=(ggplot(data=chicks) +
+ aes(x="feed",y="weight") +
+ geom_point(color="blue") +
+ theme_classic())
+print p
+
+
+
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+
+
+In [36]:
+
+
+
+
+
+
+def null(p,obs):
+ B0=p[0]
+ sigma=p[1]
+
+ expected=B0
+ nll= -1*scipy.stats.norm(expected,sigma).logpdf(obs.weight).sum()
+ return nll
+
+
+
+
+
+
+
+
+-
+
- Alternate hypothesis: +
+
+
+
+
+In [37]:
+
+
+
+
+
+
+def alter(p,obs):
+ B0=p[0]
+ B1=p[1]
+ sigma=p[2]
+
+ expected=B0+B1*obs.x # error?
+ nll= -1*scipy.stats.norm(expected,sigma).logpdf(obs.weight).sum()
+ return nll
+
+
+
+
+
+
+
+
+
+
+
+In [38]:
+
+
+
+
+
+
+chicks = pandas.read_csv("chickwts.txt")
+
+#fixed subset
+subset1 = chicks.loc[chicks['feed'].isin(['sunflower','soybean'])]
+subset1['x'] = [0 if ele == "soybean" else 1 for ele in subset1["feed"]]
+
+
+
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+
+
+
+
+
+In [39]:
+
+
+
+
+
+
+import numpy
+import scipy
+from scipy import optimize
+from scipy import stats
+from scipy.stats import norm
+
+
+
+
+
+
+
+
+The fit¶
+
+
+
+
+
+In [40]:
+
+
+
+
+
+
+initialGuess=numpy.array([1,1])
+alterGuess=numpy.array([1,1,1])
+fitNull=scipy.optimize.minimize(null,initialGuess,method="Nelder-Mead",options={'disp':True},args=subset1)
+fitAlter=scipy.optimize.minimize(alter,alterGuess,method="Nelder-Mead",options={'disp':True},args=subset1)
+print(fitNull)
+print(fitAlter)
+
+
+
+
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+
+
+
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+
+
+
+
+
+
+
+In [41]:
+
+
+
+
+
+
+#### The results
+
+
+
+
+
+In [43]:
+
+
+
+
+
+
+D=2*(fitNull.fun-fitAlter.fun)
+print "result"
+print 1-scipy.stats.chi2.cdf(x=D,df=1)
+# sunflower seed sig increases weight
+
+
+
+
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+
+
+
+
+
+In [ ]:
+
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+