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nalin [4]
3 years ago
10

2 2/7 + 4 1/2 simplified

Mathematics
2 answers:
RSB [31]3 years ago
5 0

Answer:

2 2/7 + 4 1/2

Step-by-step explanation:

Exact form 95/14 for me

Mixed number will be 6 11/14

OlgaM077 [116]3 years ago
4 0

Answer: 6 and 11/14

Step-by-step explanation:

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asambeis [7]

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W: 455 ft

L :.655 ft

Step-by-step explanation:

I did the math if it's wrong I'm so sorry but I'm 99.9% sure it's right.

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Find the equation of the line that contains the point (4,-2) and is perpendicular to the line y = – 2x + 5
velikii [3]

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Step-by-step explanation:

hope this helps if not sorry

3 0
3 years ago
What is the probability of rolling an odd number on the six-sided cube
tankabanditka [31]
It'd be a 50% chance
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What is the value of w?
sergeinik [125]

Answer:  Most likely, the value of w is 5 units.

Step-by-step explanation: P = 2L + 2w

If the perimeter is 28, the side lengths must be less than 14, otherwise there is no width, just two lines on top of one another.

If the width is 7, then all four sides would be 7 units, and <u>that would create a square</u>-- which is a type of rectangle-- but probably not what this question is about.

A width of 5 units makes sense, 2w would be 10, leaving 28-10 = 18 to be divided by 2 for lengths of 9

The rectangle would have a width of 5 units and a length of 9 units.

7 0
3 years ago
The scores of students on the ACT college entrance exam in a recent year had the normal distribution with mean  =18.6 and stand
Maurinko [17]

Answer:

a) 33% probability that a single student randomly chosen from all those taking the test scores 21 or higher.

b) 0.39% probability that the mean score for 76 students randomly selected from all who took the test nationally is 20.4 or higher

Step-by-step explanation:

To solve this question, we need 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, the sample means with size n of at least 30 can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}

In this problem, we have that:

\mu = 18.6, \sigma = 5.9

a) What is the probability that a single student randomly chosen from all those taking the test scores 21 or higher?

This is 1 subtracted by the pvalue of Z when X = 21. So

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

Z = \frac{21 - 18.6}{5.4}

Z = 0.44

Z = 0.44 has a pvalue of 0.67

1 - 0.67 = 0.33

33% probability that a single student randomly chosen from all those taking the test scores 21 or higher.

b) The average score of the 76 students at Northside High who took the test was x =20.4. What is the probability that the mean score for 76 students randomly selected from all who took the test nationally is 20.4 or higher?

Now we have n = 76, s = \frac{5.9}{\sqrt{76}} = 0.6768

This probability is 1 subtracted by the pvalue of Z when X = 20.4. So

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

By the Central Limit Theorem

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

Z = \frac{20.4 - 18.6}{0.6768}

Z = 2.66

Z = 2.66 has a pvalue of 0.9961

1 - 0.9961 = 0.0039

0.39% probability that the mean score for 76 students randomly selected from all who took the test nationally is 20.4 or higher

4 0
2 years ago
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