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3 years ago

What is the simplest form

Mathematics

1 answer:

Soloha48 [4]3 years ago

6 0

√50 + √242 - √2
= √5·5·2 + √11·11·2 -√2
= 5√2 + 11√2 - √2
= 16√2 - √2
= 15√2

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Figure LMNP will be reflected across the y-axis. Place the point on the graph that represents

zimovet [89]

Answer:

If it's reflected on the y-axis, the answer for N would be (-2,-3).

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3 years ago

PLEASE HELP WILL MARK BRAINLIEST!!!!

Lyrx [107]

Answer:

y = -5x + 20

Step-by-step explanation:

Lets start with the first given values for x and y

(2,10)

Lets try out the first equation

y = 5x + 4

y = 5(2) + 4

y = 14

This equation wouldn't work because the y value is not 10 when the x value is 2

y = 5x + 20

y = 5(2) + 20

y = 30

This equation doesn't work either

y = -5x + 20

y = -5(2) + 20

y = -10 + 20

y = 10

This would be the correct equation since your y value is 10 when the x value is 2

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2 years ago

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hichkok12 [17]

Given

1. 4 x 1/7

2. 12 x 2 5/6

procedure

$4*\frac{1}{7}$

1. The answer is 4 x 1/7 is less than 4

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2. The answer is 12 x 2 5/6 is greater than 12

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1 year ago

A ski lift is designed with a total load limit of 20,000 pounds. It claims a capacity of 100 persons. An expert in ski lifts thi

Yanka [14]

Answer:

0.5 = 50% probability that a random sample of 100 independent persons will cause an overload

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 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 sum of n values of a distribution, the mean is $\mu \times n$ and the standard deviation is $\sigma\sqrt{n}$

An expert in ski lifts thinks that the weights of individuals using the lift have expected weight of 200 pounds and standard deviation of 30 pounds. 100 individuals.

This means that $\mu = 200*100 = 20000, \sigma = 30\sqrt{100} = 300$