import numpy as np
import matplotlib.pyplot as plt

# Data:
    
y = np.array([600, 470, 170, 430, 300])
n = len(y)

# Gj.snitt:

m_y = np.sum(y)/n
print('m_y =', f'{m_y :.2f}')

# Variansen og standardavviket:

var_y = np.sum((y - m_y)**2)/(n - 1)
std_y = np.sqrt(var_y )
print('std_y =', f'{std_y :.2f}')

# Plotting:

x = np.array([1, 2, 3, 4, 5])
m_y = m_y*np.ones(5)
std_plot_pos = m_y + std_y
std_plot_neg = m_y - std_y

plt.plot(x, y, 'g*')
plt.plot(x, m_y, 'b--')
plt.plot(x, std_plot_pos, 'r')
plt.plot(x, std_plot_neg, 'r')

# plt.savefig('statistikk_hunder.pdf')
plt.show()