Answer:
1958
Explanation:
The term was first published in the 1958 Harvard Business Review when authors Harold J. Leavitt and Thomas C. Whisler said “the new technology does not yet have a single established name. We shall call it Information Technology.”
Answer:
Algorithm for the above problem:
- Take a string from the user input.
- store the input string on any variable.
- Reverse the string and store it on the other variable.
- Compare both strings (character by character) using any loop.
- If all the character of the string matched then print that the "Input string is a palindrome".
- Otherwise, print "The inputted string is not a palindrome."
Output:
- If the user inputs "ababa", then it prints that the "Input string is palindrome"
- If the user inputs "ababaff", then it prints that the "Input string is not palindrome"
Explanation:
- The above-defined line is a set of an algorithm to check the number is palindrome or not.
- It is defined in English because the algorithm is a finite set of instructions written in any language used to solve the problem.
- The above algorithm takes input from the user, compare that string with its reverse and print palindrome, if the match is found.
I've included my code in a picture below. I hope this helps.
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.
