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luda_lava [24]
2 years ago
13

If it takes 6 printing presses 4 hours to print 5000 newspapers, how long should it take 3 presses to print 3000 newspapers?

Mathematics
1 answer:
vladimir1956 [14]2 years ago
7 0

Answer:

4 hrs 48 min

Step-by-step explanation:

It takes 6 presses 4 * 3/5 = 12/5 hours to print 3000 newspapers.

It takes 3 presses 2 * 12/5 = 24/5 hours = 4h48min to print 3000 newpapers

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Answer:

<J = 75

Step-by-step explanation:

8 0
2 years ago
Identify the period for the trigonometric function: f (t) = −2sec(t).
Agata [3.3K]

Answer:

The answer is 2pi.

Hope this helps you. Also if you practice your material better you won't need to ask. Studying is the medicine to all problems xD



3 0
2 years ago
True or false: The variable overhead rate variance uses the same basic formula as the labor rate variance except that the variab
Zanzabum

Answer:

True

Step-by-step explanation:

The variable overhead rate variance refers to the difference in two variables.

The Variables are

1. The actual variable manufacturing overhead

2. The expected variable overhead given the number of hours worked

Labor rate variance is evaluated by

AH(AR - SR)

AH = actual hours

AR = actual rate

SR = standard rate.

The variable overhead rate variance is also calculated the same way except that it replaces the direct labor rates with variable overhead rates

5 0
3 years ago
An analysis of sales records for the last 120 weeks gives the following results. Assuming that these past data are a reliable gu
Mila [183]

Answer:

(a) 0.5333

(b) 0.6583

(c) 0.5583

(d) 0.7083

(e) 0.6167

Step-by-step explanation:

Denote the events as follows:

<em>A</em> = a competitor will advertise

<em>NA </em>= a competitor will not advertise

<em>L </em>= Low sales will be achieved

<em>M </em>= Medium sales will be achieved

<em>H </em>= High sales will be achieved

The data provided is of the form:

          Low (L)    Medium (M)    High (H)    Total    

A            32                   14                 18               64

NA          21                   12                 23              56

Total      53                  26                 41              120

The probability of an event <em>E</em> is:

P(E)=\frac{n(E)}{N}

n (E) = favorable outcomes of event <em>E</em>

N = Total number of outcomes

(a)

Compute the probability that next week the competitor will advertise as follows:

P(A)=\frac{n(A)}{N}=\frac{64}{120}=0.5333

Thus, the probability that next week the competitor will advertise is 0.5333.

(b)

Compute the probability that next week sales will not be high as follows:

P(H^{c})=1-P(H)=1-\frac{n(H)}{N}=1-\frac{41}{120}=\frac{120-41}{120}=0.6583

Thus, the probability that next week sales will not be high is 0.6583.

(c)

The events of achieving a medium or high sales are mutually exclusive.

Since the sales achieved will either be medium or high. They cannot be both.

So, P (M ∩ H) = 0.

Compute the probability that next week there will be medium or high sales will be achieved as follows:

P(M\cup H)=P(M)+P(H)=\frac{26}{120}+\frac{41}{120}=\frac{26+41}{120}=0.5583

Thus, the probability that next week there will be medium or high sales will be achieved is 0.5583.

(d)

Compute the probability that next week either the competitor will advertise, or only low sales will be achieved as follows:

P(A\cup L)=P(A)+P(L)-P(A\cap L)=\frac{64}{120}+\frac{53}{120}-\frac{32}{120}=\frac{85}{120}=0.7083

Thus, the  the probability that next week either the competitor will advertise, or only low sales will be achieved is 0.7083.

(e)

Compute the probability that next week either the competitor will not advertise, or high sales will be achieved as follows:

P(NA\cup H)=P(NA)+P(H)-P(NA\cap H)=\frac{56}{120}+\frac{41}{120}-\frac{23}{120}=\frac{74}{120}=0.6167

Thus, the  the probability that next week either the competitor will not advertise, or high sales will be achieved is 0.6167.

8 0
3 years ago
The probability of a couple having either a boy or a girl is ?. however, many families have more boys than girls and vice versa.
Gwar [14]
<span>The probability of having either a boy or a girl is statistically 0.5, and this makes sense at the chromosomal level - there are genetic reasons for it. 

Why the observed ratio in families is different than predicted ratio is simply due to chance. Just like getting a string of heads when you flip a coin, you got 'lucky' - not real luck but just random coincidence. Your next coin toss could be a tail.


</span>
4 0
2 years ago
Read 2 more answers
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