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Nookie1986 [14]
3 years ago
5

Darnell's car used 8 gallons of gasoline to travel 340 miles. after a mechanic worked on the car, it used 7 gallons of gasoline

to travel 350 miles. If the price of the gasoline was approximately $4.00 per gallon, how much lest to the nearst cent per mile, did it cost to run the car after the mechanic worked on it?
Mathematics
1 answer:
Ksenya-84 [330]3 years ago
3 0
So, after the mechanic worked on it, it only does 7 gallons for 350miles, how many gallons will it be at that rate, for 340 miles then?

\bf \begin{array}{ccll}
gallons&miles\\
\text{\textemdash\textemdash\textemdash}&\text{\textemdash\textemdash\textemdash}\\
7&350\\
x&340
\end{array}\implies \cfrac{7}{x}=\cfrac{350}{340}\implies \cfrac{7\cdot 340}{350}=x\implies 6.8=x

well, each gallon is 4 bucks, for 6.8 gallons that'd be 6.8*4.

we already know that before the mechanic worked on it, it was doing 8gallons for the same 340 miles, and at 4 bucks a gallon that'd be 8*4.

how much is her savings?

\bf \stackrel{\stackrel{\textit{gallons cost}}{\textit{before being fixed}}}{(8\cdot 4)}\qquad -\qquad \stackrel{\stackrel{\textit{gallons cost}}{\textit{after it was fixed}}}{(6.8\cdot 4)}
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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)

c) FALSE

d) FALSE

e) TRUE

f) 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.

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

P = 10997 / 40000 = 0.274925

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

This is a correct interpretation of a confidence interval. It indicates that if we perform sampling with same sample size (40000) several times and calculate the 95% confidence interval of population proportion for each of them, then 95% of these confidence interval should contain the population parameter.

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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