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4 years ago

I need to know how to cross simplify.

Mathematics

2 answers:

Gelneren [198K]4 years ago

3 0

Answer:

Step-by-step explanation:

Simplify the fractions. Write the simplified numerator and denominator above and below the old ones. Before you multiply, you can write another equivalent, simpler fraction in the place of a fraction.

iVinArrow [24]4 years ago

3 0

Answer:

Step-by-step explanation:

Okay, set them up

2 8

----------

4 10

You look at the 2 and the 10, can 10 be divided by 2 evenly? Yes so how many 2s are in ten? The 2 becomes a 1 because 2 divided by 2 = 1

and the 10 becomes a 5 because 10/2 = 5

Then look at the 4 and the 8. Can 8 and 4 be divided by 4? Yes, how many 4s in 4? How many 4s in 8? so the 4 becomes a 1 and the 8 becomes a 2.

New problem

1/1 x 2/5 = 2/5

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Step-by-step explanation:

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3 years ago

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What is the probability of tossing two coins in Irvington bus land on heads?

d1i1m1o1n [39]

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Answer:

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Hope you could understand.

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2 years ago

Jordan wrote a number on a piece of paper. The number is greater than 24 but less than 38. The number is even and can be divided

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Hey!
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3 years ago

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A worldwide organization of academics claims that the mean IQ score of its members is 118, with a standard deviation of 17. A ra

miss Akunina [59]

Answer:

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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 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 $s = \frac{\sigma}{\sqrt{n}}$ .