Answer:
import numpy as np
def sample_median(n, P):
return np.median( np.random.choice ( np.arange (1, len(P) + 1 ), n, p = P ) )
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(10,[0.1 0.2 0.1 0.3 0.1 0.2]))
print(sample_median(5, [0.3,0.7])
print(sample_median(5, [0.3,0.7])
Explanation:
- Bring in the numpy library to use the median function provided by the numpy library.
- Define the sample_median function that takes in 2 parameters and returns the median with the help of built-in random, choice and arrange functions.
- Call the sample_median function by providing some values to test and then display the results.
Output:
4.5
4.0
2.0
1.0
Your answer would be 6 cells
A computer BIT is the amount of data that a CPU can manipulate at one time.
Answer:
Explanation:
Meaningful decisions are important to sustaining immersion, but it's generally considered poor game design to constantly give the player "critical" decisions. Describe a game you know and how it asks the player to make a variety of decisions from the different levels of Tracy Fullerton's Decision Scale.
5 is one bigger than 4, so it is 101
Note: this doesn't always work for every number.
the binary numbers 1-8 would be: 1, 10, 11, 100, 101, 110, 111, 1000
Can you guess 9?: 1001
10?: 1010
Hope this helps, <span>and May the Force Be With You!
-Jabba
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