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yaroslaw [1]
3 years ago
12

a checheers board is 8 square long and 7 squares wide. The area of each square is 14 square centimeter. Estimate the perimeter o

f the checkers board to the nearest tenth of a centimeter

Mathematics
1 answer:
Lesechka [4]3 years ago
4 0
Turn 14 into 16, 4 x 4 = 16, 4 x 8 = 32, 32 x 4 = 128cm
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Answer:

Hope this helps. Good luck

Step-by-step explanation:

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Find the exact length for the third side
andre [41]

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12

Step-by-step explanation:

Pythagorean theorem

a²+b²=c²

a²+35²=37²

a²+1225=1369

manipulate the equation

1225-1369=-a²

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2 years ago
Please help with math
Sergio [31]

Answer: x = 2

Step-by-step explanation:

x+y=8\\y=3x

Replace y in the first equation by the value of y in the second equation.

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3 years ago
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Helga [31]

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Step-by-step explanation:

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6 0
3 years ago
A study of the amount of time it takes a mechanic to rebuild the transmission for a 1992 Chevrolet Cavalier shows that the mean
Dovator [93]

Answer:

B) 0.0069

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 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.

In this question, we have that:

\mu = 8.4, \sigma = 1.8, n = 40, s = \frac{1.8}{\sqrt{40}} = 0.2846

Find the probability that their mean rebuild time exceeds 9.1 hours.

This is 1 subtracted by the pvalue of Z when X = 9.1. So

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

By the Central Limit Theorem

Z = \frac{9.1 - 8.4}{0.2846}

Z = 2.46

Z = 2.46 has a pvalue of 0.9931

1 - 0.9931 = 0.0069

So the answer is B.

6 0
3 years ago
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