lines='obs_number,low_bw,age,weight,race,smoked,n_premature,hypertension,uterine_irritability,n_visits,birthweight_gm
  4,1,28,120,3,1,1,0,1,0, 709
 11,1,34,187,2,1,0,1,0,0,1135
 15,1,25, 85,3,0,0,0,1,0,1474
 17,1,23, 97,3,0,0,0,1,1,1588
 19,1,24,132,3,0,0,1,0,0,1729
 22,1,32,105,1,1,0,0,0,0,1818
 24,1,25,115,3,0,0,0,0,0,1893
 26,1,25, 92,1,1,0,0,0,0,1928
 28,1,21,200,2,0,0,0,1,2,1928
 30,1,21,103,3,0,0,0,0,0,1970
 32,1,25, 89,3,0,2,0,0,1,2055
 34,1,19,112,1,1,0,0,1,0,2084
 36,1,24,138,1,0,0,0,0,0,2100
 40,1,20,120,2,1,0,0,0,3,2126
 43,1,27,130,2,0,0,0,1,0,2187
 45,1,17,110,1,1,0,0,0,0,2225
 47,1,20,109,3,0,0,0,0,0,2240
 50,1,18,110,2,1,1,0,0,0,2296
 52,1,21,100,3,0,1,0,0,4,2301
 56,1,31,102,1,1,1,0,0,1,2353
 59,1,23,187,2,1,0,0,0,1,2367
 61,1,24,105,2,1,0,0,0,0,2381
 63,1,23,120,3,0,0,0,0,0,2410
 67,1,22,130,1,1,0,0,0,1,2410
 69,1,23,110,1,1,1,0,0,0,2424
 75,1,26,154,3,0,1,1,0,1,2442
 77,1,26,190,1,1,0,0,0,0,2466
 79,1,28, 95,1,1,0,0,0,2,2466
 82,1,23, 94,3,1,0,0,0,0,2495
 84,1,21,130,1,1,0,1,0,3,2495
 86,0,33,155,3,0,0,0,0,3,2551
 88,0,21,108,1,1,0,0,1,2,2594
 91,0,21,124,3,0,0,0,0,0,2622
 93,0,17,103,3,0,0,0,0,1,2637
 95,0,26,113,1,1,0,0,0,0,2665
 97,0,19,150,3,0,0,0,0,1,2733
 99,0,30,107,3,0,1,0,1,2,2750
101,0,18,100,1,1,0,0,0,0,2769
103,0,25,118,1,1,0,0,0,3,2782
 10,1,29,130,1,0,0,0,1,2,1021
 13,1,25,105,3,0,1,1,0,0,1330
 16,1,27,150,3,0,0,0,0,0,1588
 18,1,24,128,2,0,1,0,0,1,1701
 20,1,21,165,1,1,0,1,0,1,1790
 23,1,19, 91,1,1,2,0,1,0,1885
 25,1,16,130,3,0,0,0,0,1,1899
 27,1,20,150,1,1,0,0,0,2,1928
 29,1,24,155,1,1,1,0,0,0,1936
 31,1,20,125,3,0,0,0,1,0,2055
 33,1,19,102,1,0,0,0,0,2,2082
 35,1,26,117,1,1,1,0,0,0,2084
 37,1,17,130,3,1,1,0,1,0,2125
 42,1,22,130,1,1,1,0,1,1,2187
 44,1,20, 80,3,1,0,0,1,0,2211
 46,1,25,105,3,0,1,0,0,1,2240
 49,1,18,148,3,0,0,0,0,0,2282
 51,1,20,121,1,1,1,0,1,0,2296
 54,1,26, 96,3,0,0,0,0,0,2325
 57,1,15,110,1,0,0,0,0,0,2353
 60,1,20,122,2,1,0,0,0,0,2381
 62,1,15,115,3,0,0,0,1,0,2381
 65,1,30,142,1,1,1,0,0,0,2410
 68,1,17,120,1,1,0,0,0,3,2414
 71,1,17,120,2,0,0,0,0,2,2438
 76,1,20,105,3,0,0,0,0,3,2450
 78,1,14,101,3,1,1,0,0,0,2466
 81,1,14,100,3,0,0,0,0,2,2495
 83,1,17,142,2,0,0,1,0,0,2495
 85,0,19,182,2,0,0,0,1,0,2523
 87,0,20,105,1,1,0,0,0,1,2557
 89,0,18,107,1,1,0,0,1,0,2600
 92,0,22,118,1,0,0,0,0,1,2637
 94,0,29,123,1,1,0,0,0,1,2663
 96,0,19, 95,3,0,0,0,0,0,2722
 98,0,22, 95,3,0,0,1,0,0,2751
100,0,18,100,1,1,0,0,0,0,2769
102,0,15, 98,2,0,0,0,0,0,2778
104,0,20,120,3,0,0,0,1,0,2807
105,0,28,120,1,1,0,0,0,1,2821
107,0,31,100,1,0,0,0,1,3,2835
109,0,28,120,3,0,0,0,0,0,2863
112,0,28,167,1,0,0,0,0,0,2877
114,0,29,150,1,0,0,0,0,2,2920
116,0,17,113,2,0,0,0,0,1,2920
118,0,24, 90,1,1,1,0,0,1,2948
120,0,25,155,1,0,0,0,0,1,2977
123,0,29,140,1,1,0,0,0,2,2977
125,0,27,124,1,1,0,0,0,0,2922
127,0,33,109,1,1,0,0,0,1,3033
129,0,19,189,1,0,0,0,0,2,3062
131,0,21,160,1,0,0,0,0,0,3062
133,0,18, 90,1,1,0,0,1,0,3062
135,0,19,132,3,0,0,0,0,0,3090
137,0,22, 85,3,1,0,0,0,0,3090
139,0,23,128,3,0,0,0,0,0,3104
141,0,30, 95,1,1,0,0,0,2,3147
143,0,16,110,3,0,0,0,0,0,3175
145,0,30,153,3,0,0,0,0,0,3203
147,0,17,119,3,0,0,0,0,0,3225
149,0,23,119,3,0,0,0,0,2,3232
151,0,28,140,1,0,0,0,0,0,3234
155,0,20,169,3,0,1,0,1,1,3274
159,0,28,250,3,1,0,0,0,6,3303
161,0,22,158,2,0,1,0,0,2,3317
163,0,31,150,3,1,0,0,0,2,3321
166,0,16,112,2,0,0,0,0,0,3374
168,0,18,229,2,0,0,0,0,0,3402
170,0,32,134,1,1,1,0,0,4,3430
173,0,23,190,1,0,0,0,0,0,3459
175,0,32,170,1,0,0,0,0,0,3473
177,0,20,127,3,0,0,0,0,0,3487
180,0,17,120,3,1,0,0,0,0,3572
182,0,23,130,1,0,0,0,0,0,3586
184,0,22,125,1,0,0,0,0,1,3614
186,0,21,134,3,0,0,0,0,2,3629
188,0,25, 95,1,1,3,0,1,0,3637
190,0,29,135,1,0,0,0,0,1,3651
192,0,19,147,1,1,0,0,0,0,3651
195,0,30,137,1,0,0,0,0,1,3699
197,0,19,184,1,1,0,1,0,0,3756
200,0,23,110,1,0,0,0,0,1,3770
202,0,25,241,2,0,0,1,0,0,3790
204,0,22,169,1,0,0,0,0,0,3827
206,0,16,170,2,0,0,0,0,4,3860
208,0,18,120,3,0,0,0,0,1,3884
210,0,33,117,1,0,0,0,1,1,3912
212,0,28,134,3,0,0,0,0,1,3941
106,0,32,121,3,0,0,0,0,2,2835
108,0,36,202,1,0,0,0,0,1,2836
111,0,25,120,3,0,0,0,1,2,2877
113,0,17,122,1,1,0,0,0,0,2906
115,0,26,168,2,1,0,0,0,0,2920
117,0,17,113,2,0,0,0,0,1,2920
119,0,35,121,2,1,1,0,0,1,2948
121,0,25,125,2,0,0,0,0,0,2977
124,0,19,138,1,1,0,0,0,2,2977
126,0,31,215,1,1,0,0,0,2,3005
128,0,21,185,2,1,0,0,0,2,3042
130,0,23,130,2,0,0,0,0,1,3062
132,0,18, 90,1,1,0,0,1,0,3062
 34,0,32,132,1,0,0,0,0,4,3080
136,0,24,115,1,0,0,0,0,2,3090
138,0,22,120,1,0,0,1,0,1,3100
140,0,22,130,1,1,0,0,0,0,3132
 42,0,19,115,3,0,0,0,0,0,3175
144,0,21,110,3,1,0,0,1,0,3203
146,0,20,103,3,0,0,0,0,0,3203
148,0,17,119,3,0,0,0,0,0,3225
150,0,24,110,3,0,0,0,0,0,3232
154,0,26,133,3,1,2,0,0,0,3260
 56,0,24,115,3,0,0,0,0,2,3274
160,0,20,141,1,0,2,0,1,1,3317
162,0,22,112,1,1,2,0,0,0,3317
164,0,23,115,3,1,0,0,0,1,3331
167,0,16,135,1,1,0,0,0,0,3374
169,0,25,140,1,0,0,0,0,1,3416
172,0,20,121,2,1,0,0,0,0,3444
174,0,22,131,1,0,0,0,0,1,3460
176,0,30,110,3,0,0,0,0,0,3544
179,0,23,123,3,0,0,0,0,0,3544
181,0,19,105,3,0,0,0,0,0,3572
183,0,36,175,1,0,0,0,0,0,3600
185,0,24,133,1,0,0,0,0,0,3614
187,0,19,235,1,1,0,1,0,0,3629
189,0,16,135,1,1,0,0,0,0,3643
191,0,29,154,1,0,0,0,0,1,3651
193,0,19,147,1,1,0,0,0,0,3651
196,0,24,110,1,0,0,0,0,1,3728
199,0,24,110,3,0,1,0,0,0,3770
201,0,20,120,3,0,0,0,0,0,3770
203,0,30,112,1,0,0,0,0,1,3799
205,0,18,120,1,1,0,0,0,2,3856
207,0,32,186,1,0,0,0,0,2,3860
209,0,29,130,1,1,0,0,0,2,3884
211,0,20,170,1,1,0,0,0,0,3940
213,0,14,135,1,0,0,0,0,0,3941
214,0,28,130,3,0,0,0,0,0,3969
216,0,16, 95,3,0,0,0,0,1,3997
218,0,26,160,3,0,0,0,0,0,4054
220,0,22,129,1,0,0,0,0,0,4111
222,0,31,120,1,0,0,0,0,2,4167
224,0,19,120,1,1,0,0,0,0,4238
226,0,45,123,1,0,0,0,0,1,4990
215,0,25,120,1,0,0,0,0,2,3983
217,0,20,158,1,0,0,0,0,1,3997
219,0,21,115,1,0,0,0,0,1,4054
221,0,25,130,1,0,0,0,0,2,4153
223,0,35,170,1,0,1,0,0,1,4174
225,0,24,116,1,0,0,0,0,1,4593'
con = textConnection( lines )
DF = read.table( con, header=TRUE, sep=',' )
close(con)


# Part (a):
#
#postscript("../../WriteUp/Graphics/Chapter10/ex_3_two_densities.eps", onefile=FALSE, horizontal=FALSE) 
par(mfrow=c(2,1)) 
plot( density( DF$birthweight_gm, adjust=1.0 ), main='adjust=1' )
plot( density( DF$birthweight_gm, adjust=0.6 ), main='adjust=0.6' ) # gives a long left tail with a hump to the left of the main hump
par(mfrow=c(1,1))
#dev.off()

#postscript("../../WriteUp/Graphics/Chapter10/ex_3_densities_by_BW.eps", onefile=FALSE, horizontal=FALSE)
lbw = DF$low_bw == 1
nbw = DF$low_bw != 1
plot( density( DF[lbw,]$birthweight_gm ), col='red', xlim=range(DF$birthweight_gm), main='' ) 
lines( density( DF[nbw,]$birthweight_gm ), col='green', main='' )
legend( 3750, 0.0012, legend=c("low BW", "normal BW"), col=c('red', 'green'), lty=c(1,1) )
grid()
#dev.off()

# For prediction we want to look at which variables are the most correlated with LB:
# (dropping the one obviously not important)
#
df = DF
df$obs_number = NULL
df$birthweight_gm = NULL
c = cor( df )
row = c[,1]
print( t( row[ order(abs(row), decreasing=TRUE), drop=FALSE ] ) )