No, -8 - 2(3 + 2n) + 7n is not equivalent to -30 - 13n
Step-by-step explanation:
Let us revise the operation of the negative and positive numbers
- (-) + (-) = (-)
- (-) × (-) = (+)
- (-) + (+) = the sign of greatest [(-) if the greatest is (-) or (+) if the greatest is (+)]
- (-) × (+) = (-)
- (-) - (+) = (-)
- (+) - (-) = (+)
∵ The expression is -8 - 2(3 + 2n) + 7n
- Simplify it
∵ 2(3 + 2n) = 2(3) + 2(2n) = 6 + 4n
∴ -8 - 2(3 + 2n) + 7n = -8 - (6 + 4n) + 7n
- Multiply the bracket by (-)
∴ -8 - (6 + 4n) + 7n = -8 - 6 - 4n + 7n
- Add the like terms
∴ -8 - (6 + 4n) + 7n = (-8 - 6) - 4n + 7n
∴ -8 - (6 + 4n) + 7n = -14 + 3n
∴ -8 - 2(3 + 2n) + 7n is equivalent to -14 + 3n
∵ -14 + 3n ≠ -30 - 13n
∴ -8 - 2(3 + 2n) + 7n is not equivalent to -30 - 13n
No, -8 - 2(3 + 2n) + 7n is not equivalent to -30 - 13n
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Answer:
Step-by-step explanation:
Part A.
Expression
= 10
Because 100 =
and ![[(10)^2]^{\frac{1}{2}}=10^1=10](https://tex.z-dn.net/?f=%5B%2810%29%5E2%5D%5E%7B%5Cfrac%7B1%7D%7B2%7D%7D%3D10%5E1%3D10)
[Since,
]
Part B.
When simplified, the answer is RATIONAL.
[Since, 10 can be written as
]
Answer:
P(X ≥ 1) = 0.50
Step-by-step explanation:
Given that:
The word "supercalifragilisticexpialidocious" has 34 letters in which 'i' appears 7 times in the word.
Then; the probability of success = 7/34 = 0.20588
Using Binomial distribution to determine the probability; we have:

where;
x = 0,1,2,...n and 0 < β < 1
and x represents the number of successes.
However; since the letter is drawn thrice; the probability that the letter "i" is drawn at least once can be computed as:
P(X ≥ 1) = 1 - P(X< 1)
P(X ≥ 1) = 1 - P(X =0)
![P(X \ge 1) = 1 - \bigg [ {^3C__0} (0.21)^0 (1-0.21)^{3-0} \bigg]](https://tex.z-dn.net/?f=P%28X%20%5Cge%201%29%20%3D%20%201%20-%20%5Cbigg%20%5B%20%7B%5E3C__0%7D%20%280.21%29%5E0%20%281-0.21%29%5E%7B3-0%7D%20%5Cbigg%5D)
![P(X \ge 1) = 1 - \bigg [ 1 \times 1 (0.79)^{3} \bigg]](https://tex.z-dn.net/?f=P%28X%20%5Cge%201%29%20%3D%20%201%20-%20%5Cbigg%20%5B%201%20%5Ctimes%201%20%280.79%29%5E%7B3%7D%20%5Cbigg%5D)
P(X ≥ 1) = 1 - 0.50
P(X ≥ 1) = 0.50