Quiz assignment for week 1 of Regression



In [3]:

    
%matplotlib inline



In [7]:

    
import matplotlib.pyplot as plt
import numpy as np



In [6]:

    
plt.plot([1,2,3,4])
plt.ylabel('some numbers')
plt.show()



In [8]:

    
def graph(formula, x_range):  
    x = np.array(x_range)  
    y = eval(formula)
    plt.plot(x, y)  
    plt.show()



In [36]:

    
graph('4569+143*x', range(0, 20))



In [24]:

    
def valueInMonth(x):
    intercept = 4569
    slope = 143
    return intercept + slope * x



In [25]:

    
valueInMonth(10)









    Out[25]:





5999



In [26]:

    
valueInMonth(52)









    Out[26]:





12005



In [28]:

    
def housePriceRegression(x):
    intercept = -44850
    slope = 280.76
    return intercept + x * slope

The intercept stays the same while the slope changes depending on the units of both features and observations



In [33]:

    
280.76 / 0.092903 # Something is wrong









    Out[33]:





3022.076789769975



In [37]:

    
280.76 * 10









    Out[37]:





2807.6



In [38]:

    
3022.076789769975 * 0.9290304









    Out[38]:





2807.601208830716



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