1. Import the necessary packages to read in the data, plot, and create a linear regression model



In [1]:

    
import pandas as pd
import matplotlib.pyplot as plt
%matplotlib inline
import statsmodels.formula.api as smf









    



/usr/lib/python2.7/dist-packages/matplotlib/font_manager.py:273: UserWarning: Matplotlib is building the font cache using fc-list. This may take a moment.
  warnings.warn('Matplotlib is building the font cache using fc-list. This may take a moment.')

2. Read in the hanford.csv file



In [2]:

    
df=pd.read_csv('/home/sean/git/algorithms/class6/data/hanford.csv')

3. Calculate the basic descriptive statistics on the data



In [15]:

    
df



In [3]:

    
df.describe()

4. Calculate the coefficient of correlation (r) and generate the scatter plot. Does there seem to be a correlation worthy of investigation?



In [22]:

    
lm = smf.ols(formula="Mortality~Exposure",data=df).fit()

5. Create a linear regression model based on the available data to predict the mortality rate given a level of exposure



In [23]:

    
lm.params









    Out[23]:





Intercept    114.715631
Exposure       9.231456
dtype: float64



In [28]:

    
intercept, slope = lm.params

6. Plot the linear regression line on the scatter plot of values. Calculate the r^2 (coefficient of determination)



In [30]:

    
df.plot(kind="scatter",x="Exposure",y="Mortality", linewidths=0)
plt.plot(df["Exposure"],slope*df["Exposure"]+intercept,"-",color="red")









    Out[30]:





[<matplotlib.lines.Line2D at 0x7f8b3c634590>]



In [31]:

    
r_squared=slope**2

7. Predict the mortality rate (Cancer per 100,000 man years) given an index of exposure = 10



In [32]:

    
exposure=input("Enter county exposure:")
print("Expected mortality rate:", (slope*exposure)+intercept)









    



Enter county exposure:10
('Expected mortality rate:', 207.03019352841989)



In [ ]:

	County	Exposure	Mortality
0	Umatilla	2.49	147.1
1	Morrow	2.57	130.1
2	Gilliam	3.41	129.9
3	Sherman	1.25	113.5
4	Wasco	1.62	137.5
5	HoodRiver	3.83	162.3
6	Portland	11.64	207.5
7	Columbia	6.41	177.9
8	Clatsop	8.34	210.3

	Exposure	Mortality
count	9.000000	9.000000
mean	4.617778	157.344444
std	3.491192	34.791346
min	1.250000	113.500000
25%	2.490000	130.100000
50%	3.410000	147.100000
75%	6.410000	177.900000
max	11.640000	210.300000