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2 years ago

14

Every day, Bert spends an hour commuting to and from his office, driving at an average speed of 50 mph and taking the same route

each way. How far does Bert live from his office?

1 answer:

Ira Lisetskai [31]2 years ago

7 0

About 45 miles and if you have options choose the closest to45 miles

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A craftsman can sell 10 jewelry sets for $500 each. He knows

liraira [26]

Answer:15

Step-by-step explanation:

Given

Craftsman sell 10 Jewelry set for $500 each

For each additional set he will decrease the price by $ 25

Suppose he sells n set over 10 set

Earning $=\text{Price of each set}\times \text{no of set}$

Earning $=(500-25n)(10+n)$

$E=5000+500n-25n^2-250n$

differentiate to get the maximum value

$\frac{dE}{dn}=-50n+250$

Equate $\frac{dE}{dn}$ to get maximum value

$-50n+250=0$

$n=\frac{250}{50}$

$n=5$

Thus must sell 5 extra set to maximize its earnings.

5 0

1 year ago

A computer uses 239 watts per hour. How many watts would it use if it is on for 8 days?

Serjik [45]

29 watts hope this helps

4 0

2 years ago

Dan is fourteen years older than Marge. Eight years ago, Dan was three times as old as Marge. Find their present age.

34kurt

Answer:

<u>Marge's</u> present age = 14 ; <u>Dan's</u> present age = 29

Step-by-step explanation:

Present age

Let Marge's present age be = M

Dan's present age [D] : 14 years elder than Marge = M + 14

8 years ago

Marge Age = M - 8

Dan's Age = D - 8 = (M + 14) - 8 = M + 6

{Given} : Dan's age = 3 times Marge's age

M + 6 = 3 (M - 8)

M + 6 = 3M - 24

6 + 24 = 3M - M

30 = 2M

M = 30/2

M = 15 [Marge's present age]

Dan's present age [D] = M + 14 = 29

5 0

1 year ago

Customers are used to evaluate a preliminary product design. In the past, 95% of highly successful products received good review

Sever21 [200]

Answer:

a. 61.5%; b. About 61.8%; c. About 36.4%

Step-by-step explanation:

This is a kind of question that we can solve using the Bayes' Theorem. We have here all the different conditional probabilities we need to solve this problem.

According to that theorem, the probability of a selected product attains a good review is:

$\\ P(G) = P(G|H)*P(H) + P(G|M)*P(M) + P(G|P)*P(P)$ (1)

In words, the probability that a selected product attains a <em>good review</em> is an <em>event </em>that depends upon the sum of the conditional probabilities that the product comes from <em>high successful product</em> P(G|H) by the probability that this product is a <em>highly successful product</em> P(H), plus the same about the rest of the probabilities, that is, P(G|M)*P(M) or the probability that the product has a good review coming from a <em>moderately successful</em> product by the probability of being moderately successful, and a good review coming from a poor successful product by the probability of being poor successful or P(G|P)*P(P).

<h3>The probability that a randomly selected product attains a good review</h3>

In this way, the probability that a randomly selected product attains a good review is the result of the formula (1). Where (from the question):

P(G|H) = 95% or 0.95 (probability of receiving a good review being a highly successful product)

P(G|M) = 60% or 0.60 (probability of receiving a good review being a moderately successful product)

P(G|P) = 10% or 0.10 (probability of receiving a good review being a poorly successful product)

P(H) = 40% or 0.40 (probability of being a highly successful product).

P(M) = 35% or 0.35 (probability of being a moderately successful product).

P(P) = 25% or 0.25 (probability of being a poor successful product).

Then,

$\\ P(G) = P(G|H)*P(H) + P(G|M)*P(M) + P(G|P)*P(P)$

$\\ P(G) = 0.95*0.40 + 0.60*0.35 + 0.10*0.25$

$\\ P(G) = 0.615\;or\; 61.5\%$

That is, <em>the probability that a randomly selected product attains a good review</em> is 61.5%.

<h3>The probability that a new product attains a good review is a highly successful product</h3>

We are looking here for P(H|G). We can express this probability mathematically as follows (another conditional probability):

$\\ P(H|G) = \frac{P(G|H)*P(H)}{P(G)}$

We can notice that the probability represents a fraction from the probability P(G) already calculated. Then,

$\\ P(H|G) = \frac{0.95*0.40}{0.615}$

$\\ P(H|G) =\frac{0.38}{0.615}$

$\\ P(H|G) =0.618$

Then, the probability of a product that attains a good review is indeed a highly successful product is about 0.618 or 61.8%.

<h3>The probability that a product that <em>does not attain </em>a good review is a moderately successful product</h3>

The probability that a product does not attain a good review is given by a similar formula than (1). However, this probability is the complement of P(G). Mathematically:

$\\ P(NG) = P(NG|H)*P(H) + P(NG|M)*P(M) + P(NG|P)*P(P)$

P(NG|H) = 1 - P(G|H) = 1 - 0.95 = 0.05

P(NG|M) = 1 - P(G|M) = 1 - 0.60 = 0.40

P(NG|P) = 1 - P(G|M) = 1 - 0.10 = 0.90

So

$\\ P(NG) = 0.05*0.40 + 0.40*0.35 + 0.90*0.25$

$\\ P(NG) = 0.385\;or\; 38.5\%$

Which is equal to

P(NG) = 1 - P(G) = 1 - 0.615 = 0.385

Well, having all this information at hand:

$\\ P(M|NG) = \frac{P(NG|M)*P(M)}{P(NG)}$

$\\ P(M|NG) = \frac{0.40*0.35}{0.385}$

$\\ P(M|NG) = \frac{0.14}{0.385}$

$\\ P(M|NG) = 0.363636... \approx 0.364$

Then, the <em>probability that a new product does not attain a good review and it is a moderately successful product is about </em>0.364 or 36.4%.

8 0

1 year ago

Under ideal conditions a certain bacteria population is known to double every three hours. Suppose that there are initially 100

lara [203]

Answer:

the estimation of the size of the population after 20 hours is 10159

Step-by-step explanation:

The computation of the size of the population after 20, hours is shown below;

= 100 2^(20 by 3)

= 10159.36

If we divide 20 by 3 so it would give 6.66 that lies between 6 and 7

So the estimation of the size of the population after 20 hours is 10159

hence, the same is relevant

3 0

1 year ago

Read 2 more answers