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2 years ago

Please help me with this question I really need help!!!!!!!!!!!!!!!!!!!!!!!!!!!!

Mathematics

1 answer:

Alinara [238K]2 years ago

6 0

Answer:

Step-by-step explanation:

The angles of a triangle add up to 180°.

∠4 = 180°-35°-90° = 55°

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e-lub [12.9K]

Answer: E: 100%

Step-by-step explanation:

If the class average is currently 70% and she wants to increase it by 10% every week for 3 weeks, 10×3=30% and 70+30= 100%.

PS- It would mean the world to me if you could mark me brainliest!

I am not a professional, I am simply using prior knowledge!

7 0

2 years ago

Can somebody help me I’m stuck with this!!

Mama L [17]

I believe it’s A, C, and E

3 0

2 years ago

Can anyone answer this problem in their head. No calculator or paper.

rodikova [14]

7,393,420,225 is the answer tk the problem without using calculator.

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3 years ago

If you shift the quadratic parent function, Flx) =x, down 9 units, what is the equation of the new function?

Mashutka [201]

Answer:

y = x-9

Step-by-step explanation:

6 0

2 years ago

Suppose a shipment of 400 components contains 68 defective and 332 non-defective computer components . From the shipment you tak

Alona [7]

Answer:

The standard deviation for the number of defective parts in the sample is 1.88.

Step-by-step explanation:

The sample is with replacement, which means that the trials are independent, and thus, the binomial probability distribution is used to solve this question.

Binomial probability distribution

Probability of exactly x successes on n repeated trials, with p probability.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

68 defective out of 400:

This means that $p = \frac{68}{400} = 0.17$

From the shipment you take a random sample of 25.

This means that $n = 25$

Standard deviation for the number of defective parts in the sample:

$\sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{25*0.17*0.83} = 1.88$

The standard deviation for the number of defective parts in the sample is 1.88.

6 0

2 years ago