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3 years ago

CAN SOMEONE PLEAEE HELP ????!!!!!! I will mark Brianliest !!!!!!!!!!!!!!!!!!

Mathematics

2 answers:

Salsk061 [2.6K]3 years ago

8 0

Answer:

59°

Step-by-step explanation:

According to the given description, $\angle QRS$ is the exterior angle of $\triangle PQR$

So, by exterior angle property of a triangle, we have:

$m\angle QRS=m\angle RPQ+m\angle PQR\\\\(10x - 1)\degree = (3x +17)\degree+(2x +12)\degree\\\\(10x - 1)\degree = (3x +17+2x +12)\degree\\\\(10x - 1)\degree = (5x +29)\degree\\\\(10x - 1)= (5x +29)\\\\10x - 5x = 29 + 1\\\\5x = 30\\\\x = \frac{30}{5}\\\\x = 6\\\\\because m\angle QRS = (10x - 1)\degree \\\\\therefore m\angle QRS = (10\times 6- 1)\degree \\\\\therefore m\angle QRS = (60- 1)\degree \\\\\huge\orange{\boxed{\therefore m\angle QRS = 59\degree }}\\$

enyata [817]3 years ago

7 0

Answer:

I don't know if I'm correct but the answer is 6.

Step-by-step explanation:

I'm not 100% correct, but you set the other two angles to add to each other then set it equal to angle QRS and i got x=6.

Your equation should be like this: 3x + 17 + 2x +21 = 10x -1

than you solve form there

I;m not sure that this is the correct answer and maybe i'm wrong, but hope this helps

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Answer:

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Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".

Solution to the problem

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Where $\mu=17.5$ and $\sigma=4$

Since the distribution for X is normal then, the distribution for the sample mean $\bar X$ is given by:

$\bar X \sim N(\mu= 17.5, \frac{\sigma}{\sqrt{n}}= \frac{4}{\sqrt{50}}=0.566)$

We select a sample of n =50 people. And we want to find the following probability

$P(16.5$

And using the normal standard table or excel we find the probability:

$P(-1.768< Z< 1.768) = P(Z$

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