To convert 345 millimeters to liters,which proportion should I use?

Mathematics

1 answer:

Usimov [2.4K]3 years ago

3 0

I think number 2 not sure tho

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A choir with 8 members sings ave Maria in 8mins how long for 20 members to sing

liubo4ka [24]

Answer:20

Step-by-step explanation:

8 members=8mins

1 member=80 mins

20members=2.5mins

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2 years ago

A crew will arrive in one week and begin filming a city for a movie. The mayor is desperate to clean the city streets before fil

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Step-by-step explanation:

1 week = 7 days of 24 hours each = 7×24 = 168 hours.

the first team can do 1/700 of the total work per hour.

the second team can do 1/600 if the total work per hour.

if they work together, then 1/700 + 1/600 of the total work can be done per hour.

to add these 2 fractions we need to bring them to the same denominator. and that would be 4200 (LCM of 700 and 600).

1/700 + 1/600 = 6/4200 + 7/4200 = 13/4200

so, together, they can do 13/4200 if the total job in 1 hour.

how many hours will they need together to finish the job ?

well, how often does 13 fit into 4200 (as 4200/4200 is the complete job) ?

4200 / 13 = 323.0769231... hours

so, it will still take a little bit over 323 hours to clean all the streets.

but there are only 168 hours until the film crew starts.

so, no, there is not enough time.

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2 years ago

The line graph with gradient 2 and y-intercept(0,5)

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Answer:

The line graph is:

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3 years ago

A score that is three standard deviations above the mean would have a z score of

tia_tia [17]

The value of z-score for a score that is three standard deviations above the mean is 3.

In this question,

A z-score measures exactly how many standard deviations a data point is above or below the mean. It allows us to calculate the probability of a score occurring within our normal distribution and enables us to compare two scores that are from different normal distributions.

Let x be the score

let μ be the mean and

let σ be the standard deviations

Now, x = μ + 3σ

The formula of z-score is

$z_{score} = \frac{x-\mu}{\sigma}$