Answer: On the same page
Explanation:
The CRM is basically stand for the customer relationship management that are design to support all the relationship with the customers. It basically analysis the data about the customers to improve the relationship and growth in the organization.
All the employees in the organization are directly and indirectly server the customers are basically o the Same page by the individual computers.
The CRM approach are basically compile the given data from the different communication source such as company website, email and telephone.
Answer:
128 is ur answer
Explanation:
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Answer:
False
Explanation:
High quality page for a common interpretation always have different Needs Met rating than the high quality page for a minor interpretation of the query.
Although, both of this pages are of high quality we must differentiate the common from a minor interpretation of a query.
Needs Met should always know to place the high quality pages in a resolution hierarchy.
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.