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N76 [4]
3 years ago
12

When derivative classifiers incorporate classified information from existing content into a document and no additional interpret

ation or analysis is needed to deduce the classification of that inform?
Mathematics
1 answer:
Tju [1.3M]3 years ago
4 0

Answer:

The answer to this question is Contained in:

Step-by-step explanation:

This concept involves the extraction of classified information the same way it was stated in the authorized document or classification source without adding any other information, analysis , or interpretation, and inserting same information into a new document.

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3 years ago
1. A gambler makes 100 column bets at roulette. The chance of winning on any one play is 12/38. The gambler can either win $ 5 o
lapo4ka [179]

Answer:

a) Expected amount of the gambler's win = $0.209

b) SD = 2.26

c)P (X >1) = P(z >0.35) = 0.36317

Step-by-step explanation:

The probability of winning, p = 12/38 =6/19

Probability of losing, q = 1 -p = 1-6/19

q = 13/19

Win amount = $5

Loss amount = $2

a) Expected total amount of win = ((6/19)*5) - ((13/19)*2)

Expected total amount of win = 1.579 - 1.369

Expected amount of win, E(X) = $0.209

b) Standard Deviation for the total amount of the gambler's win

SD = \sqrt{E(X^{2}) - (E(X))^{2} }

E(X²) = (6/19)*5²  -  (13/19)*2²

E(X²) = 5.158

SD = \sqrt{5.158 - 0.209^2}

SD = 2.26

c)  probability that, in total, the gambler wins at least $1.

P(X >1)

z = \frac{X - \mu}{\sigma}

μ = E(x) = 0.209

z = (1-0.209)/2.26

z = 0.35

P( X >1) = P(z >0.35)

P(z >0.35) = 1 - P(z <0.35)

P(z >0.35) = 1 - 0.63683

P(z >0.35) = 0.36317

5 0
3 years ago
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