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Naya [18.7K]
3 years ago
14

Hurry please I need help on this

Mathematics
1 answer:
lubasha [3.4K]3 years ago
5 0
5/6-2/5 would be my guess

beacuse i would think the answer would be 1/3 but that is not on the multiple choice.




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I thnk 83 if the year has 365 days

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7

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Hi please help i’ll give brain
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Answer:

The GCF is going to be 30

Step-by-step explanation:

This Is how I find the GCF of 2 numbers. I find the prime factorization first, then I find the common factors and multiply them. Here

The prime factorization of 21, 2 × 3 × 3 × 5= 90

The prime factorization of 28, 2 × 3 × 5 × 7 = 210

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The distribution of resistance for resistors of a certain type is known to be normal, with 10% of all resistors having a resista
baherus [9]

Answer:

The mean is 9.65 ohms and the standard deviation is 0.2742 ohms.

Step-by-step explanation:

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.

10% of all resistors having a resistance exceeding 10.634 ohms

This means that when X = 10.634, Z has a pvalue of 1-0.1 = 0.9. So when X = 10.634, Z = 1.28.

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

1.28 = \frac{10.634 - \mu}{\sigma}

10.634 - \mu = 1.28\sigma

\mu = 10.634 - 1.28\sigma

5% having a resistance smaller than 9.7565 ohms.

This means that when X = 9.7565, Z has a pvalue of 0.05. So when X = 9.7565, Z = -1.96.

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

-1.96 = \frac{9.7565 - \mu}{\sigma}

9.7565 - \mu = -1.96\sigma

\mu = 9.7565 + 1.96\sigma

We also have that:

\mu = 10.634 - 1.28\sigma

So

10.634 - 1.28\sigma = 9.7565 + 1.96\sigma

1.96\sigma + 1.28\sigma = 10.645 - 9.7565

3.24\sigma = 0.8885

\sigma = \frac{0.8885}{3.24}

\sigma = 0.2742

The mean is

\mu = 10.634 - 1.28\sigma = 10 - 1.28*0.2742 = 9.65

The mean is 9.65 ohms and the standard deviation is 0.2742 ohms.

8 0
3 years ago
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