Question

reproduce the output in p.75 and figure p.77(use Python )

Table 3.1: headsize data. Head Size Data. 157 195 163 176 146 head1 breadth1 head2 breadth 2 head1 breadth1 head2 breadth 2 191 155 179 145 190 159 195 149201 152 188 151 187 158 181 148 185 1491 137 161 130 183 153 188 149 195 155 183 158 144 171 142 186 153 173 148 208 157 192 152 181 145 182 189 150 190 149 175 140 165 137 197 159 189 152 192 154 185 152 197 159 174 143 178 147 192 150 187 151 176 139176 143 179 158 186 148) 197 167 200 158 183 147 174 1471 190 163 187 150 174 150 185 152 152 188 The data in Table 3.1 give the head lengths and head breadths (in millimetres) for each of the first two adult sons in 25 families. Here we shall use only the head lengths; the head breadths will be used later in the chapter. The mean vector and covariance matrix of the head length measurements are found using

compute the principle ( read the R -code ) and do it on python with figure

just convert the code to python

I want to do it in Python program, please don't waste my time just tell me exactly you want

Answer 1

import matplotlib.pyplot as plt
import numpy as np

head1 = ([191,195,181,183,176,208,189,197,188,192,179,183,174,190,188,163,195,186,181,175,192,174,176,197,190])
head2 = ([179,201,185,188,171,192,190,189,197,187,186,174,185,195,187,161,183,173,182,165,185,179,176,200,187])

a1 = 183.84-0.721*185.72/0.693
b1 = 0.721/0.693
a2 = 183.84 - (-0.693*185.72/0.721)
b2 = -0.693/0.721

x = np.linspace(min(head1),max(head1),5)
plt.scatter(head1,head2)
plt.plot(x,a1 + b1*x)
plt.plot(x,a2 + b2*x,linestyle= '--')
plt.xlabel("First son's head length (mm)")
plt.ylabel("Second son's head length")
plt.show()

In [20]: import matplotlib.pyplot as plt import numpy as np head1 = ([191,195,181,183,176,208,189,197,188,192,179, 183, 174, 190, 188,163,195,186,181,175, 192,174,176, 197, 190]) head2 = ([179, 281,185,188,171,192,190,189,197,187,186,174,185,195,187,161,183,173,182,165, 185, 179,176,200,1871) al = 183.84-0.721 185.72/2.693 bi = 0.721/0.693 a2 = 183.84 - (-0.6938185.72/0.721) b2 = -0.693/0.721 X = np.linspace(min(headi), max(headı),5) plt.scatter (headı, head2) plt.plot(x, a1 + b1*x) plt.plot(x, a2 + b2*x, linestyle='..') plt.xlabel("First son's head length (mm)") plt.ylabel("Second son's head length") pit. show Second son's head length 170 180 190 First son's head length (mm) 200 210