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3 years ago

Find the input (x) of the function y = -4/3x+ 20 if the output (y) is -80

Mathematics

1 answer:

RideAnS [48]3 years ago

4 0

Answer:

x=75

Step-by-step explanation:

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Plz help :( what is 10,000,000(20)^10 !?

Sergio [31]

Answer: 102,400,000,000,000,000,000

Step-by-step explanation:

First do 20^10 = 10,240,000,000,000.

Then, multiply 10,240,000,000,000 * 10,000,000 to get 102,400,000,000,000,000,000.

<em>Hope it helps <3</em>

7 0

3 years ago

Help pls will give 10 points

patriot [66]

Answer:

In the picture

Step-by-step explanation:

I hope that it's a clear explanation.

4 0

3 years ago

Please help me solve this

Tema [17]

Answer:

Step-by-step explanation:

I think it is she sped up and passed susana since it shows it in the graph.

5 0

3 years ago

At the burger place, 3 mini hamburgers fit in each small to-go bag. if the baldwin family ordered 41 mini hamburgers for the tri

arsen [322]

How man bags were used?

41 / 3 = 13.7

We can say about 14 bags by rounding to the nearest whole number. Therefore, 14 bags were used.

5 0

3 years ago

Read 2 more answers

Suppose a certain type of fertilizer has an expected yield per acre of mu 1 with variance sigma 2, whereas the expected yield fo

mart [117]

Answer:

See the proof below.

Step-by-step explanation:

For this case we just need to apply properties of expected value. We know that the estimator is given by:

$S^2_p= \frac{(n_1 -1) S^2_1 +(n_2 -1) S^2_2}{n_1 +n_2 -2}$

And we want to proof that $E(S^2_p)= \sigma^2$

So we can begin with this:

$E(S^2_p)= E(\frac{(n_1 -1) S^2_1 +(n_2 -1) S^2_2}{n_1 +n_2 -2})$

And we can distribute the expected value into the temrs like this:

$E(S^2_p)= \frac{(n_1 -1) E(S^2_1) +(n_2 -1) E(S^2_2)}{n_1 +n_2 -2}$

And we know that the expected value for the estimator of the variance s is $\sigma$ , or in other way $E(s) = \sigma$ so if we apply this property here we have:

$E(S^2_p)= \frac{(n_1 -1 )\sigma^2_1 +(n_2 -1) \sigma^2_2}{n_1 +n_2 -2}$

And we know that $\sigma^2_1 = \sigma^2_2 = \sigma^2$ so using this we can take common factor like this:

$E(S^2_p)= \frac{(n_1 -1) +(n_2 -1)}{n_1 +n_2 -2} \sigma^2 =\sigma^2$

And then we see that the pooled variance is an unbiased estimator for the population variance when we have two population with the same variance.

8 0

3 years ago