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bogdanovich [222]
3 years ago
9

????DAY is a rhombus. If point ???? has coordinates (2, 6) and ???????? has coordinates (8, 10), what is the

Mathematics
1 answer:
satela [25.4K]3 years ago
7 0

Please dont put question mark on these they dont make sense so make thi sbetter!

Please!

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(4n-3n^3)-(3n^3+4n) answer
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I hope this helps you

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Which expression represents the sum of (2x-5y and (x+y) ?
gayaneshka [121]
I have no clue you have to do something like x2-x1 over y1-y2 and you get yoyu answer from that. 
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
For what values of x does the binomial 2x−1 take on a positive value?
Mashutka [201]
1). 2x-1>0
2x>1
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2) 21-3y<0
-3y<-21
y>7

3) 5-3c>80
-3c>75
c<-25
3 0
3 years ago
Simplify the numerical expression 9+3 x 8
Komok [63]

Answer:

33

Step-by-step explanation:

9+3*8=9+24=33

3 0
3 years ago
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