Answer:
i think its b
Explanation:
i did the test and got it right
A partial dependency exists.
We have two types of dependency. The partial dependency and the transitive dependency.
The answer here is partial dependency. It occurs when the attribute only depends on some parts of the element. In such attribute, the primary key is the determinant.
It can be shown as;
XY→WZ , X→W and XY is the primary key or the only candidate key
Read more at brainly.com/question/9588869?referrer=searchResults
Can u plz give me a picture
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/
hjlf
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
Good job! please mark as branliest?!