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levacccp [35]
2 years ago
8

Construct a polynomial function with the following properties: fifth degree, 2 is a zero of multiplicity 4, −2 is the only other

zero, leading coefficient is 3.
Mathematics
1 answer:
MrMuchimi2 years ago
5 0

9514 1404 393

Answer:

  p(x) = 3(x -2)^4(x +2) . . . in factored form

  p(x) = 3x^5 -18x^4 +24x^3 +48x^2 -144x +96  . . . in standard form

Step-by-step explanation:

When a polynomial has a zero at x=p, it has a factor of (x -p). The exponent of the factor is the multiplicity of the zero. The product of factors can be multiplied by 3 to make the leading coefficient be 3.

  p(x) = 3(x -2)^4(x -(-2))

  = 3(x^4 +4(-2)x^3 +6(-2)^2x^2 +4(-2)^3x +(-2)^4)·(x +2)

  = 3(x^4 -8x^3 +24x^2 -32x +16)(x +2)

  = 3(x^5 -6x^4 +8x^3 +16x^2 -48x +32)

  p(x) = 3x^5 -18x^4 +24x^3 +48x^2 -144x +96

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Answer:

x = 4

Step-by-step explanation:

we know that 72 and (2x + 10) add up to 90

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Penelope is going to the carnival to ride the rides. It costs $20 to get into the
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Answer:

35=0.5x+20

Step-by-step explanation:

y=mx+b

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3 years ago
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Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}, in which \mu is the mean life expectancy, \sigma is the standard deviation and n is the size of the sample.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

We have:

Mean \mu, standard deviation \sigma.

Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

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The probability that the mean life expectancy of the sample is less than X years is the p-value of Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}, in which \mu is the mean life expectancy, \sigma is the standard deviation and n is the size of the sample.

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Answer

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Step-by-step explanation:

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