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Andreas93 [3]
2 years ago
7

PLEASE HELP!!!!!!!!!!!!!!!!!!!!

Mathematics
2 answers:
aleksklad [387]2 years ago
4 0
1: 5-3 2: 3-1 3: 1+1
alekssr [168]2 years ago
3 0
X= 4-2
X= 6-4
X = 8-6
Is this what u want?
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Question: How is dividing 250 by 50 the same as dividing 2,500 by 500?
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Well dont you have to bring down the zeros than you will have the answer
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The first three steps in determining the solution set of the system of equations algebraically are shown.
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Since both are equivalent to y, the equations must be equivalent.
x^2-x-3= -3x+5
x^2+2x-8=0

(x+4)(x-2)=0
x=-4, x=2

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y=-3(-4)+5
y= 12+5
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y= -3(2)+5
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Final answer: (-4,17) and (2,-1)
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A square room in Amber's home has an area of 128 square feet. Which is the best estimate of one side length of the room?
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Based on historical data, your manager believes that 37% of the company's orders come from first-time customers. A random sample
fomenos

Answer:

0.6214 = 62.14% probability that the sample proportion is between 0.26 and 0.38

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}}.

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}}

37% of the company's orders come from first-time customers.

This means that p = 0.37

A random sample of 225 orders will be used to estimate the proportion of first-time-customers.

This means that n = 225

Mean and standard deviation:

\mu = p = 0.37

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.37*0.63}{225}} = 0.0322

What is the probability that the sample proportion is between 0.26 and 0.38?

This is the pvalue of Z when X = 0.38 subtracted by the pvalue of Z when X = 0.26.

X = 0.38

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

By the Central Limit Theorem

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

Z = \frac{0.38 - 0.37}{0.0322}

Z = 0.31

Z = 0.31 has a pvalue of 0.6217

X = 0.26

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

Z = \frac{0.26 - 0.37}{0.0322}

Z = -3.42

Z = -3.42 has a pvalue of 0.0003

0.6217 - 0.0003 = 0.6214

0.6214 = 62.14% probability that the sample proportion is between 0.26 and 0.38

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2 years ago
In a reflection, pairs of corresponding points lie on parallel lines.<br> True or False?
Lerok [7]

The statement that: pairs of corresponding points lie on parallel lines in a reflection, is false.

<h3>What are reflections?</h3>

When a point is reflected, then the point is flipped across a point or line of reflection

When a point is reflected, the following highlights are possible

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Using the above highlights, we can conclude that the statement is false.

This is so because, corresponding points are not always on parallel lines

Read more about reflection at:

brainly.com/question/23970016

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