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hammer [34]
4 years ago
11

How many cubes with the side lengths of 1/2 cm does it take to fill the prisim?

Mathematics
1 answer:
My name is Ann [436]4 years ago
8 0

Answer:

Number of cubes that fills the prism=24

Step-by-step explanation:

The number of cube that completely fill the prism=Volume of Prism/Volume of cube with side 1/2 cm=0.5 cm

Volume of  the prism=Length*Width*Height

Length=2 cm\\\\    Width=1 cm\\   \\ Height=3/2 cm = 1.5 cm

Volume of Prism = 2*1*1.5

                      =3.0 cm^3

Volume of the Cube:

                                    Side*Side*Side\\\\=0.5*0.5*0.5

                                      = 0.125 cm^3

Number of cubes that fills the prism:

                                        3.0/0.125\\\\=24 cubes

So, the number of cubes that can fill the prism is '24'

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3 years ago
According to data released by FiveThirty Eight (data drawn on Monday, August 17th, 2020), Donald Trump wins an Electoral College
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Answer:

a) P = 0.274925

b) required confidence interval = (0.2705589, 0.2793344)

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d) FALSE

e) TRUE

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Step-by-step explanation:

a)

PROBABILITY

since total number of simulations is 40,000 and and number of times Donald Trump wins an Electoral College majority in the 2020 US Presidential Election is  10,997

so the required Probability will be 10,997 divided by 40,000

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b)

To get 95% confidence interval for the parameter in question a

(using R)

>prop.test(10997,40000)

OUTPUT

1 - Sample proportion test with continuity correction

data: 10997 out of 40000, null probability 0.5

x-squared = 8104.5, df = 1, p-value < 2.23-16

alternative hypothesis : true p ≠ 0.5

0.2705589  0.2793344

sample estimate

p

0.274925

∴ required confidence interval = (0.2705589, 0.2793344)

c)

FALSE

This is a wrong interpretation of a confidence interval. It indicates that there is 95% chance that the confidence interval you calculated contains the true proportion. This is because when you perform several times, 95% of those intervals would contain the true proportion but as the confidence intervals will vary so you can't say that the true proportion is in any interval with 95% probability.

d)

FALSE

Once again, this is a wrong interpretation of a confidence interval. The confidence interval tells us about the population parameter and not the sample statistic.

e)

TRUE

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f)

The simulation results obtained doesn't always comply with the true population. Also, result of one simulation can't be taken for granted. We need several simulations to come to a conclusion. So, we can never ever guarantee based on a simulation result to say that Donald Trump 'Won't' or 'Shouldn't' win.

There is still probability that he would win. And it would be highly unusual if he wins assuming that the true population proportion is 0.274925.

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