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Travka [436]
3 years ago
15

Put this numbers from least to greatest.

Mathematics
2 answers:
murzikaleks [220]3 years ago
8 0

Answer:

A: 9, 3.2, 1.78, 0.67

B: 6, 7/8, 3/4, 1/2, 1/4

all together 9, 6, 3.2, 1.78, 7/8, 3/4, 0.67, 1/2, 1/4

Step-by-step explanation:

Galina-37 [17]3 years ago
6 0

Answer:

1/4, 1/2, .67, 3/4, 7/8, 1.78, 3.2, 6, 9

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According to data released by FiveThirty Eight (data drawn on Monday, August 17th, 2020), Donald Trump wins an Electoral College
sineoko [7]

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.

5 0
3 years ago
7g – 2g + g + 3g = 18
In-s [12.5K]
G = 2

Hope This Is Sufficient !!
5 0
3 years ago
Read 2 more answers
2.654,2.564,2.056,2.465 from greatest to least
marusya05 [52]
2.654, 2.564,2.465, 2.065
8 0
3 years ago
Read 2 more answers
Round 3.44570830811 to the nearest hundred-thousandth,
Alika [10]

Answer:

3.44571

Step-by-step explanation:

look at the number to the right of the decimal. if the number is higher than or is 5 round the number up, but if the number is less than 5 it will stay the same.

4 0
3 years ago
Which data collections show bias? Check all that apply.
V125BC [204]

Answer:

An insurance company polls drivers of sports cars to find their average number of tickets.

Step-by-step explanation:

It’s bias because they’re only polling people with sports cars

7 0
3 years ago
Read 2 more answers
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