Laws differ from theories because laws do not provide an explanation for how things work or could possibly work. A law describes what happens or needs to happen under certain conditions. A law can predict what will happen as long as those conditions are met. <span>For the purposes of this discussion, a "law" is a rule that has been formalised by repeated testing. It is also a generalisation. A theory, on the other hand, is an explanation for an observation that is supported by a large body of evidence. </span>
Answer:
import numpy as np
import matplotlib.pyplot as plt
def calculate_pi(x,y):
points_in_circle=0
for i in range(len(x)):
if np.sqrt(x[i]**2+y[i]**2)<=1:
points_in_circle+=1
pi_value=4*points_in_circle/len(x)
return pi_value
length=np.power(10,6)
x=np.random.rand(length)
y=np.random.rand(length)
pi=np.zeros(7)
sample_size=np.zeros(7)
for i in range(len(pi)):
xs=x[:np.power(10,i)]
ys=y[:np.power(10,i)]
sample_size[i]=len(xs)
pi_value=calculate_pi(xs,ys)
pi[i]=pi_value
print("The value of pi at different sample size is")
print(pi)
plt.plot(sample_size,np.abs(pi-np.pi))
plt.xscale('log')
plt.yscale('log')
plt.xlabel('sample size')
plt.ylabel('absolute error')
plt.title('Error Vs Sample Size')
plt.show()
Explanation:
The python program gets the sample size of circles and the areas and returns a plot of one against the other as a line plot. The numpy package is used to mathematically create the circle samples as a series of random numbers while matplotlib's pyplot is used to plot for the visual statistics of the features of the samples.
You should first .<span>consider how you could shorten the column labels.
Shortening the column labels could be easily done by dragging the column to the size that we want. But when shortening the column labels, some problems might occur such as the content might be distorted and in will become unevenly placed.</span>
Answer:
job search
Explanation:
job search bc you can look for jobs that are avalible online.