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3 years ago

Ac and bd are perpendicular bisectors of each other. find the perimeter of ADE

Mathematics

2 answers:

11Alexandr11 [23.1K]3 years ago

6 0

ADE should be corresponding

GrogVix [38]3 years ago

4 0

AC and BD are perpendicular bisectors of each other.

=> ABCD is rhombus.

AD = 13

AE = √(13^2 - 12^2) = 5

<h2>the perimeter of triangle ADE = 13+12+5 = 30</h2>

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Which algebraic expression is equivalent to the expression below 6(2x+5)+4x

Veronika [31]

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2 years ago

Write an equation in slope intercept form of the line with a slope of -3/4 and y intercept of -5

raketka [301]

Given,
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3 years ago

What’s the pattern of -1, -8, -27, and -64

AURORKA [14]

Hello from MrBillDoesMath!

Answer:

a(n) = (-n)^3 where n = 1,2,3,...

Discussion:

The pattern 1,8,27, 64... is immediately recognizable as the the cube of the positive integers. But this question has a minus sign appearing before each entry, suggesting we try this:

- 1 = (-1)^3

-8 = (-2)^3

-27 = (-3)^3

-64 = (-4)^3

That's what the problem statement asked for . The answer is equivalently

-1 * (n^3)

Thank you,

MrB

6 0

3 years ago

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 $s = \sqrt{\frac{p(1-p)}{n}}$