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devlian [24]
2 years ago
15

11. Higher Order Thinking Cora makes this

Mathematics
1 answer:
9966 [12]2 years ago
8 0

Step-by-step explanation:

With no photo of the design is imposible to calculate exactly the design area. However:

We know that the area of a square is:

A_{sq}=L^2 where L is the leght of the square's side

Also, the area a triangle is:

A_{tr}=\frac{h*b}{2} where h is the height and b is the base (see the figure)

So, the total area, assuming that all square tiles are equal between them (the same for the triangular ones):

A_{total}=A_{sq}*n_{squaretiles}+A_{tr}*n_{triangtiles}

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This is the most hardest question I have seen but I think it may probably be  25

Step-by-step explanation:

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Find the value of x. please explain your answer:)
marshall27 [118]

Answer:

x=16

Step-by-step explanation:

we know that 3x+2=50 according to complemntary  angles.

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If i'm in 9th grade right now what years was my 6th grade year ?
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2 years ago
A manufacturer knows that their items have a normally distributed length, with a mean of 15.4 inches, and standard deviation of
Masteriza [31]

Answer:

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

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 normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 15.4 inches, and standard deviation of 3.5 inches.

This means that \mu = 15.4, \sigma = 3.5

16 items are chosen at random

This means that n = 16, s = \frac{3.5}{\sqrt{16}} = 0.875

What is the probability that their mean length is less than 16.8 inches?

This is the p-value of Z when X = 16.8. So

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

By the Central Limit Theorem

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

Z = \frac{16.8 - 15.4}{0.875}

Z = 1.6

Z = 1.6 has a p-value of 0.9452.

0.9452 = 94.52% probability that their mean length is less than 16.8 inches.

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2 years ago
4 (5x-3) -64 (3-x) -3 (12x-4)=96
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Are you trying to simply the equation if so x = 6
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