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Dovator [93]
3 years ago
12

What is 20.9/9.31? No need to explain. Just need the answer

Mathematics
2 answers:
Furkat [3]3 years ago
3 0
2.24489795918
Is the answer
Aleks04 [339]3 years ago
3 0
Just use your calculator

answer is  2.2449  to the nearest ten thousandth
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A scale on a map is 1mm: 50miles
mixer [17]
I don’t know what the question is, your just saying that
4 0
3 years ago
In the problem 4x + 10 list a term, factor, coefficient, and constant.​
kifflom [539]

term- 4x and 10

This is because to be a term it has to be + or -

Factor- 4x+10

This is because that is what is happening in the problem

Coefficient- 4y

I don't know what the constant would be, But I hope that this helps you

6 0
3 years ago
2. Which expression is equivalent to 20+64
MaRussiya [10]

Answer:

20+64=84

40+44=84

74+10=84

30+54=84

Step-by-step explanation:

(pls mark brainliest if u can)

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4 0
3 years ago
The mean per capita income is 16,127 dollars per annum with a variance of 682,276. What is the probability that the sample mean
MakcuM [25]

Answer:

0.60% probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

Step-by-step explanation:

To solve this question, we have to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples are 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.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean \mu and standard deviation \sigma, a large sample size can be approximated to a normal distribution with mean \mu and standard deviation, which is also called standard error s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

The standard deviation is the square root of the variance. So

\mu = 16127, \sigma = \sqrt{682276} = 826, n = 476, s = \frac{826}{\sqrt{476}} = 37.86

What is the probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

Either it differs by 104 or less dollars, or it differs by more than 104 dollars. The sum of the probabilities of these events is 100. I am going to find the probability that it differs by 104 or less dollars first.

Probability that it differs by 104 or less dollars first.

pvalue of Z when X = 16127 + 104 = 16231 subtracted by the pvalue of Z when X = 16127 - 104 = 16023. So

X = 16231

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

By the Central Limit Theorem

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

Z = \frac{16231 - 16127}{37.86}

Z = 2.75

Z = 2.75 has a pvalue of 0.9970

X = 16023

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

Z = \frac{16023 - 16127}{37.86}

Z = -2.75

Z = -2.75 has a pvalue of 0.0030

0.9970 - 0.0030 = 0.9940

99.40% probability that it differs by 104 or less.

What is the probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

p + 99.40 = 100

p = 0.60

0.60% probability that the sample mean would differ from the true mean by more than 104 dollars if a sample of 476 persons is randomly selected

7 0
3 years ago
Drag the expression that is the most reasonable measurement for each object.
Luba_88 [7]

Answer:

the firs box goes in the elephant one

Step-by-step explanation:

7 0
3 years ago
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