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erma4kov [3.2K]

3 years ago

10

Bob is 3 years older than twiceJohn's age. The sum of their ages is 33. How old is Bob? B = 21 +3 J J + 2] +3=33 3J+3=33 -Be-3 C

-3 3:

1 answer:

Gwar [14]3 years ago

3 0

Answer:

23

Step-by-step explanation:

1. according to the condition 'Bob is 3 years older than twiceJohn's age':

B-2J=3;

2. according to the condition 'The sum of their ages is 33':

B+J=33

3. If to solve these two equations as a system, then

$\left \{ {{B+J=33} \atop {B-2J=3}} \right. \ => \left \{ {{B=23} \atop {J=10}} \right.$

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A simple random sample of 110 analog circuits is obtained at random from an ongoing production process in which 20% of all circu

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Answer:

64.56% probability that between 17 and 25 circuits in the sample are defective.

Step-by-step explanation:

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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:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .

In this problem, we have that:

$n = 110, p = 0.2$

So

$\mu = E(X) = np = 110*0.2 = 22$

$\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{110*0.2*0.8} = 4.1952$

Probability that between 17 and 25 circuits in the sample are defective.

This is the pvalue of Z when X = 25 subtrated by the pvalue of Z when X = 17. So

X = 25

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

$Z = \frac{25 - 22}{4.1952}$

$Z = 0.715$

$Z = 0.715$ has a pvalue of 0.7626.

X = 17

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

$Z = \frac{17 - 22}{4.1952}$

$Z = -1.19$

$Z = -1.19$ has a pvalue of 0.1170.

0.7626 - 0.1170 = 0.6456

64.56% probability that between 17 and 25 circuits in the sample are defective.

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How many ways can you distribute $4$ identical balls among $4$ different boxes?

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3 years ago

Based on the polynomial remainder theorem, what is the value of the function when x=−6 ?

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ANSWER

$f( - 6) = 10$

EXPLANATION

The given function is
$f(x) = {x}^{4} + 8 {x}^{3} + 10 {x}^{2} - 7x + 40$

According to the remainder theorem,

$f( - 6) = R$
where R is the remainder when
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We therefore substitute the value of x and evaluate to obtain,

$f( - 6) = { (- 6)}^{4} + 8 {( - 6)}^{3} + 10 { (- 6)}^{2} - 7( - 6)+ 40$

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This will evaluate to,

$f( - 6) = 10$

Hence the value of the function when
$x = - 6$

is
$10$

According to the remainder theorem,
$10$
is the remainder when

$f(x) = {x}^{4} + 8 {x}^{3} + 10 {x}^{2} - 7x + 40$
is divided by
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