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3 years ago

What is 9.2 written as a whole number in simplest form

1 answer:

3 0

9.2 Written as a whole number would just be 9, because you are simplifying/rounding the number to the nearest whole. This answer would be 9. Hope this helps o/

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Apply the distributive property to create an equivalent expression.

VMariaS [17]

Answer:

12e minus 6f minus 8

Step-by-step explanation:

I think, ... you would just double everything because the 2 yeah.. that's right

7 0

3 years ago

Read 2 more answers

I need the answers for 1 a-d pleas

DaniilM [7]

We want to find a fraction that is between

$\frac{1}{4}\:and\:\frac{1}{2}$

There are several ways to go about this.

There are also infinitely many fractions that can be found between the given fractions.

Let us go for the one in the middle of the two fractions.

So we add the two fractions and divide by 2.

a) $\frac{\frac{1}{4} +\frac{1}{2} }{2}$

Find LCM for the numerator

$\frac{\frac{1+2}{4}}{2}$

Simplify:

$\frac{\frac{3}{4}}{2}$

$\frac{\frac{3}{2}}{2}$

$\frac{3}{8}}$

b) $\frac{\frac{1}{3} +\frac{3}{4} }{2}=\frac{13}{24}$

c) $\frac{\frac{1}{2} +\frac{3}{4} }{2}=\frac{5}{8}$

d) $\frac{\frac{3}{5} +\frac{7}{8} }{2}=\frac{59}{80}$

4 0

3 years ago

If the radius and the slant height of a right circular cone are each multiplied by 9, by what factor is the surface area of the

goblinko [34]

Answer:

the answer is D) 81

7 0

3 years ago

Suppose 44% of the children in a school are girls. If a sample of 727 children is selected, what is the probability that the sam

Harman [31]

Answer:

0.9484 = 94.84% probability that the sample proportion of girls will be greater than 41%

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 establishes 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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$