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.
Answer & Explanation:
The formula in the cell B7 would be:
"=B5-B6"
And now we will press "Ctrl+C" to copy the formula in the Cell B7. After copying we will select the cell range C7 to D7 and press "Ctrl+V" to paste this formula in the cell C7:D7 and then will press Enter key. Now what we see is results in C7:D7 which we can check in our calculator whether these are corectly calculated or not.
Well since it’s a chart based on a PivotTable prettyyyy sure it’s gonna be a PibltChart
The answer, im prettysure, is d. typeface.
hope this helps (:
