Answer:
The Notebook, Beauty and the Beast, Step Brother, The Breakfast Club and The Little Mermaid
Explanation:
Answer:
A,C,D,E are the answers at least on the test i took
Explanation:
Answer:
20
Explanation:
assuming the print statement is not indented, the program effectively calculates 2+5+6+7.
The range(...) is <em>excluding </em>the end value (8 in this case).
Answer:
Whereas lines of competition are clearly defined in the more established industries, in the Internet industry they are blurred and indistinct, as companies that compete one day may be partners the next. So "Lines" cannot be compared to/with internet companies.
Explanation:
The Internet Industry is shaped by its unique framework outlining and its own rules between the companies within it, which offer a vast number of products and services and not always competing with each other compared with the traditional established industries competition lines that were developed from two parties or more aiming the same unshareable goal. These industries are stablishing the lines of competitions predicament which by all means can not be measured and applied using the same criteria for both of them.
The online industry is claiming for flexible, pliant lines of competition to be inforced to its specific logic and mechanisms.
The companies are now in a brand new competing ground with the digital area, so traditional established bart lines of competition although clear and defined are becoming obsolete facing the current surprising thus blurred and indistict internet industry lines.
Implement the simulation of a biased 6-sided die which takes the values 1,2,3,4,5,6 with probabilities 1/8,1/12,1/8,1/12,1/12,1/
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Answer:
see explaination
Explanation:
import numpy as np
import matplotlib.pyplot as plt
a = [1, 2, 3, 4, 5, 6]
prob = [1.0/8.0, 1.0/12.0, 1.0/8.0, 1.0/12.0, 1.0/12.0, 1.0/2.0]
smls = 1000000
rolls = list(np.random.choice(a, smls, p=prob))
counts = [rolls.count(i) for i in a]
prob_exper = [float(counts[i])/1000000.0 for i in range(6)]
print("\nProbabilities from experiment : \n\n", prob_exper, end = "\n\n")
plt.hist(rolls)
plt.title("Histogram with counts")
plt.show()
check attachment output and histogram