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Salsk061 [2.6K]
4 years ago
7

Write the polynomial as a product: p2q+r2–pqr–pr

Mathematics
2 answers:
Assoli18 [71]4 years ago
6 0

{p}^{2} q +  {r}^{2}  - pqr -  pr \\  = pq(p - r) - r(p - r) \\  = (pq - r)(p - r)

nikklg [1K]4 years ago
3 0

Answer:

(p - r)(pq - r)

Step-by-step explanation:

P = p²q + r² – pqr – pr  

Rewrite the equation in descending orders of p and increasing orders of r.

P = p²q - pqr - pr + r²

Factor the first two and the last two terms

P = pq(p - r) - r(p - r)

Remove the common factor

P = (p - r)(pq - r)

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Determining probability of events. please help! ​
tia_tia [17]

Answer:

23/90

Step-by-step explanation:

  1. 55/90 + 12/90 = 67/90
  2. 90 - 67 = 23
  3. 23/90

23/90 balls are green or white

i hope this helps!

6 0
4 years ago
(1 3/4 + 2 3/8) + 5 7/8=
In-s [12.5K]

Answer:

10

Step-by-step explanation:

4 0
3 years ago
Which expression shows the result of applying the distributive property to 12(5y+4)?
7nadin3 [17]

Answer:

60y+48

Step-by-step explanation:

8 0
3 years ago
The product of a number and 4 increased by 16 is -2
Thepotemich [5.8K]
This is some simple Algebra
So it's 4x+16=-2
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4x=-18
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5 0
4 years ago
Thompson and Thompson is a steel bolts manufacturing company. Their current steel bolts have a mean diameter of 144 millimeters,
kkurt [141]

Answer:

0.0524 = 5.24% probability that the sample mean would differ from the population mean by more than 2 millimeters.

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.

Mean diameter of 144 millimeters, and a variance of 49.

This means that \mu = 144, \sigma = \sqrt{49} = 7

Sample of 46:

This means that n = 46, s = \frac{7}{\sqrt{46}}

Wat is the probability that the sample mean would differ from the population mean by more than 2 millimeters?

Above 144 + 2 = 146 or below 144 - 2 = 142. Since the normal distribution is symmetric, these probabilities are equal, which means that we find one of them and multiply by two.

Probability the sample mean is below 142:

p-value of Z when X = 142, so:

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

By the Central Limit Theorem

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

Z = \frac{142 - 144}{\frac{7}{\sqrt{46}}}

Z = -1.94

Z = -1.94 has a p-value of 0.0262

2*0.0262 = 0.0524

0.0524 = 5.24% probability that the sample mean would differ from the population mean by more than 2 millimeters.

8 0
3 years ago
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