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3 years ago

Solve by factoring p² + 16p +64 = 0 i like highkey don’t know how to do this

Mathematics

2 answers:

inysia [295]3 years ago

8 0

Answer:

That factors into:

(p +8) * (p +8) =0

Therefore, p = -8 and p = -8

Step-by-step explanation:

bonufazy [111]3 years ago

7 0

Answer:

-8

Step-by-step explanation:

When you factor, you just find two numbers that add to be the first number (16) and multiply to be the second number (64). 8 and 8 both do this. So when we factor, we also add the variable into each equation because it also has been divided into two equations, and we get: (p + 8)(p +8). Notice that the equations are "+8" and not "-8" because two +8s add to give us a +16 and multiply to give us a +64. After that, we just solve the two equations to find the solutions. Subtract 8 from each equation (we do the opposite operation because 8 is positive) to get -8. Because the answer for each equation is the same our answer is -8.

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Answer:

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Step-by-step explanation:

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3 years ago

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Answer:

68.79% probability that more than 79% of the sample diamonds fail to qualify as gemstone grade

Step-by-step explanation:

We use the binomial approximation to the normal to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

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Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .