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Mathematics

1 answer:

goldenfox [79]2 years ago

8 0

Answer:

I/rt =P

Step-by-step explanation:

to get ride of the r and t u need to divide

divide by rt

which would =to I/rt=P

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Alexus [3.1K]

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29) Adam’s sister wants to watch her intake of fat per day. Here is a guideline of the recommended daily allowances. Typical val

ziro4ka [17]

Basically all the information in this problem is useless. They included all those numbers to confuse you. If you read throughly you can see that all you need to know is that Adam's sister can only have 70 grams of fat each day and that her dinner will have 48 grams of fat.

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is/of=x/100
Your trying to figure out what is 48 percent of 70 because that's how much Adam's sister is going to eat at dinner. So your is would be 48 and your of is 70. When you substitute those numbers your formula becomes 48/70=x/100. Now you cross multiply and get 70x=4800.All that's left is to divide 70 on both sides. Which gives you 68.57.The final answer is 69 percent.

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Read 2 more answers

Bottles filled by a certain machine are supposed to contain 12 oz of liquid. In fact the fill volume is random with mean 12.01 o

stepan [7]

Answer:

27.43% probability that the mean volume of a random sample of 144 bottles is less than 12 oz.

Step-by-step explanation:

To solve this problem, it is important 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 $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$