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ANEK [815]
2 years ago
9

What is the product? (9 t minus 4)(negative 9 t minus 4) negative 81 t squared minus 16 negative 81 t squared + 16 negative 81 t

squared minus 72 t + 16 negative 81 t squared + 72 t + 16
Mathematics
2 answers:
liraira [26]2 years ago
7 0

The product is negative 81 t squared + 16 ⇒ 2nd answer

Step-by-step explanation:

The product of two binomials (ax + b)(cx + d), where a, b, c, and d are constant

  • Multiply (ax) by (cx) ⇒ 1st × 1st
  • Multiply (ax) by (d) and (b) by (cx) ⇒ ext-reams and nears
  • Add the two products ⇒ like terms
  • Multiply (b) by (d) ⇒ 2nd × 2nd

Let us find the product of (9 t - 4) and (-9 t - 4)

Multiply the 1st two terms

∵ (9 t)(-9 t) = -81 t²

Multiply the ext-reams

∵ (9 t)(-4) = -36 t

Multiply the nears

∵ (-4)(-9 t) = 36 t

Add the like terms

∵ -36 t + 36 t = 0

Multiply the 2nd two terms

∵ (-4)(-4) = 16

Write the answer

∴ (9 t - 4)(-9 t - 4) = -81 t² + 0 + 16

∴ (9 t - 4)(-9 t - 4) = -81 t² + 16

The product is  -81 t² + 16

Learn more:

You can learn more about the product of algebraic expressions in brainly.com/question/1617787

#LearnwithBrainly

antoniya [11.8K]2 years ago
3 0

Answer:

b

Step-by-step explanation:

instead of reading all that ^

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Ugo [173]

Answer:

Yes, he made a reasonable inference by saying about 25 percent of students choose the science.

Step-by-step explanation:

Given that

Number of students for survey = 50

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Now as Mr. Yule said "about 25" percent of students choose the science it can be treated as reasonable approximation.

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7 0
2 years ago
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Arlecino [84]
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The time for a visitor to read health instructions on a Web site is approximately normally distributed with a mean of 10 minutes
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Answer:

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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.

Normally distributed with a mean of 10 minutes and a standard deviation of 2 minutes.

This means that \mu = 10, \sigma = 2

Suppose 64 visitors independently view the site.

This means that n = 64,  = \frac{2}{\sqrt{64}} = 0.25

a. The expected value and the variance of the mean time of the visitors.

Using the Central Limit Theorem, mean of 10 and variance of (0.25)^2 = 0.0625.

b. The probability that the mean time of the visitors is within 15 seconds of 10 minutes.

15 seconds = 15/60 = 0.25 minutes, so between 9.75 and 10.25 seconds, which is the p-value of Z when X = 10.25 subtracted by the p-value of Z when X = 9.75.

X = 10.25

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

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{10.25 - 10}{0.25}

Z = 1

Z = 1 has a p-value of 0.8413.

X = 9.75

Z = \frac{X - \mu}{s}

Z = \frac{9.75 - 10}{0.25}

Z = -1

Z = -1 has a p-value of 0.1587.

0.8413 - 0.1587 = 0.6826.

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c. The value exceeded by the mean time of the visitors with probability 0.01.

The 100 - 1 = 99th percentile, which is X when Z has a p-value of 0.99, so X when Z = 2.327.

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X = 10.58

So 10.58 minutes.

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Answer:

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Step-by-step explanation:

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We have to find the derivative of r(t) to get the tangent line:

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