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yan [13]
3 years ago
5

a speck of dust is 1.2 x 10^-6m wide. Which of the following is the best way to rewrite this quantity, using more appropriate un

its? I will Make you brainiest to the first one who answers it. A. 1.2 x 10^-4 b.1.2 x 10^-6 c.1.2 x 10^-3 d 1.2 x 10^-9
Mathematics
2 answers:
Radda [10]3 years ago
4 0

Answer:C 1.2x 10^-6

Step-by-step explanation:

Pavlova-9 [17]3 years ago
3 0

Answer:

C.

Step-by-step explanation:

Hope this helps.

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How many centimeters are there in 1/5 of an inch
Lynna [10]

Answer:

0.508

Step-by-step explanation:

4 0
3 years ago
Please help! Thank you!
Bezzdna [24]

Answer

I know the answer but i can not write it all out so i will say the last one is greatest the next to last one is in the right spot and switch the first two

Step-by-step explanation:

Sorry couldn't help too much

8 0
3 years ago
Suppose that 20% of the residents in a certain state support an increase in the property tax. An opinion poll will randomly samp
aleksklad [387]

Answer:

95.44% probability the resulting sample proportion is within .04 of the true proportion.

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.

For the sampling distribution of the sample proportion in sample of size n, the mean is \mu = p and the standard deviation is s = \sqrt{\frac{p(1-p)}{n}}

In this question:

p = 0.2, n = 400

So

\mu = 0.2, s = \sqrt{\frac{0.2*0.8}{400}} = 0.02

How likely is the resulting sample proportion to be within .04 of the true proportion (i.e., between .16 and .24)?

This is the pvalue of Z when X = 0.24 subtracted by the pvalue of Z when X = 0.16.

X = 0.24

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

By the Central Limit Theorem

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

Z = \frac{0.24 - 0.2}{0.02}

Z = 2

Z = 2 has a pvalue of 0.9772.

X = 0.16

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

Z = \frac{0.16 - 0.2}{0.02}

Z = -2

Z = -2 has a pvalue of 0.0228.

0.9772 - 0.0228 = 0.9544

95.44% probability the resulting sample proportion is within .04 of the true proportion.

6 0
3 years ago
Read 2 more answers
What is the value of ▲ in the equation shown?<br> 7x9=(7x10)-(7x▲ )
ahrayia [7]

Step-by-step explanation:

▲ =1

easy peasy........

7 0
3 years ago
PLEASE HELP NEED HELP!
nataly862011 [7]
X is across and Y is up and down
0,5 2,4 4,3 6,2 8,1 10,0
4 0
2 years ago
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