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KatRina [158]
3 years ago
5

The number 15, 56 rounded to the nearest thousand is 15,000. Which numbers could be the missing digit?

Mathematics
2 answers:
Akimi4 [234]3 years ago
7 0

If the number is 15,_56 where a single digit (0-9) goes in that blank space, then the possible answers are: 0, 1 ,2, 3, or 4.

The thousands place is the first 5 shown in the given number. The digit just next to that will determine how we round. This digit is in the hundreds place. If the hundreds digit is between 0 and 4, then we replace every digit after that first 5 with 0s. So we go from 15,_56 to 15,000

If the hundreds digit is 5, 6, 7, 8, or 9, then we round up to the nearest thousand to jump up to 16,000. This is because something like 15,556 or 15,656 is much closer to 16,000 than 15,000

Virty [35]3 years ago
4 0

The numbers 0, 1, 2, 3, 4 could all be the missing digit because they're all numbers that round down. hope this helped!

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2 years ago
A television station plans to ask a random sample of 400 city residents if they can name the news anchor on the evening news at
hodyreva [135]

Answer:

There is an 8.38% probability that the anchor will be fired.

Step-by-step explanation:

For each resident, there is only two possible outcomes. Either they can name the news anchor on the evening news at their station, or they cannot.

This means that the binomial probability distribution will be used in our solution.

However, we are working with samples that are considerably big. So i am going to aaproximate this binomial distribution to the normal.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

400 city residents are going to be asked. So n = 400.

Suppose that in fact 12% of city residents could name the anchor if asked. This means that p = 0.12.

So,

\mu = E(X) = 400*0.12 = 48

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{400*0.12*0.88} = 6.5.

They plan to fire the news anchor if fewer than 10% of the residents in the sample can do so.

What is the approximate probability that the anchor will be fired?

10% of the residents is 0.10*400 = 40 residents.

Fewer than 10% is 39 residents. So the probability that the anchor will be fired is the pvalue of Z when X = 39.

So:

Z = \frac{X - \mu}{\sigma}

Z = \frac{39 - 48}{6.5}

Z = -1.38

Z = -1.38 has a pvalue of 0.0838. This means that there is an 8.38% probability that the anchor will be fired.

5 0
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Answer:

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Step-by-step explanation:

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Step-by-step explanation:

ok

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