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skelet666 [1.2K]
3 years ago
9

How do u convert 3.54 ug to grams

Mathematics
1 answer:
denis23 [38]3 years ago
4 0
"ug" stands for microgram. You can convert microgram into grams by multiplying a certain factor. For this case, 1 microgram is known to be 1x10^-6 g. This is the conversion factor that will be multiplied to 3.54.

3.54 ug ( 1x10^-6 g / 1 ug ) = 3.54 <span>x10^-6 g</span>
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I would say Right, Isosceles.

Step-by-step explanation:

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The lengths of the sides of a triangle are 2x+1, 3x-2, and 4x-5. what is the perimeter in terms of x
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Step-by-step explanation:

2X + 1 + 3X - 2 + 4X - 5 = 180

9X - 6 = 180

9X = 174

9   =   174

ـــــــــــــــــــــ

9         9

X = 19.333

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The average score of all golfers for a particular course has a mean of 75 and a standard deviation of 4. Suppose 64 golfers play
Vilka [71]

Answer:

0.0228 = 2.28% probability that the average score of the 64 golfers exceeded 76.

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 problem, we have that:

\mu = 75, \sigma = 4, n = 64, s = \frac{4}{\sqrt{64}} = 0.5

Find the probability that the average score of the 64 golfers exceeded 76.

This is 1 subtracted by the pvalue of Z when X = 64.

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

By the Central Limit Theorem

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

Z = \frac{76 - 75}{0.5}

Z = 2

Z = 2 has a pvalue of 0.9772

1 - 0.9772 = 0.0228

0.0228 = 2.28% probability that the average score of the 64 golfers exceeded 76.

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3 years ago
Given:
lisov135 [29]

Answer:

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Step-by-step explanation:

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