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tino4ka555 [31]
2 years ago
9

This table shows equivalent ratios which ratios are equivalent to the ratios in the table check all that apply ?

Mathematics
1 answer:
Vera_Pavlovna [14]2 years ago
3 0
20:4 and 40:8 I think
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true

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Do any of you know how to do this
Gre4nikov [31]

Answer:

(x + 5)

Step-by-step explanation:

{x}^{2}  + 8x + 15 \\  {x}^{2}  + 3x + 5x + 15 \\ x(x + 3)5(x + 3) \\ (x + 3)(x + 5) \\ length \:  =  \frac{(x + 3)(x + 5)}{(x + 3)}  \\   \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \:  \: = (x  + 5)

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WILL<br><br><br> GIVE <br><br> BRAINLIST <br><br> ANSWERS
enot [183]

Answer:

-10

-I-8I = -8

-(-2) = 4

I-11I  = 11

5² = 25

Answer: -10, -8, 4, 11, 25

6 0
3 years ago
9. A business records its net profits for the week by subtracting the operating costs from the revenue. The function P(x) = (140
guapka [62]

Answer:

Profit Function, P(x) Total Income minus Total Cost. Profit ... The next unit will make this Revenue. Marginal Cost Function, C'(x) The next unit will be this Cost ... A manufacturing company produces and sells tables. The cost function is given by: where x is the number of tables. The tables are sold for $200 each. Find . 1. The total cost of ...

Step-by-step explanation:

6 0
2 years ago
A sample of 900900 computer chips revealed that 66f% of the chips fail in the first 10001000 hours of their use. The company's p
Alik [6]

Answer:

No, there is not enough evidence at the 0.02 level to support the manager's claim.

Step-by-step explanation:

We are given that the company's promotional literature states that 68% of the chips fail in the first 1000 hours of their use. Also, a sample of 900 computer chips revealed that 66% of the chips fail in the first 1000 hours of their use.

And the quality control manager wants to test the claim that the actual percentage that fail is different from the stated percentage, i.e;

Null Hypothesis, H_0 : p = 0.68 {means that the actual percentage that fail is same as the stated percentage}

Alternate Hypothesis, H_1 : p  0.68 {means that the actual percentage that fail is different from the stated percentage}

The test statistics we will use here is;

     T.S. = \frac{\hat p -p}{\sqrt{\frac{\hat p(1- \hat p)}{n} } } ~ N(0,1)

where, p = actual percentage of chip fail = 0.68

            \hat p = percentage of chip failed in a sample of 900 chips = 0.66

           n = sample size = 900

So, Test statistics = \frac{0.66 -0.68}{\sqrt{\frac{0.66(1- 0.66)}{900} } }

                             = -1.267

Now, at 0.02 significance level, the z table gives critical value of -2.3263 to 2.3263. Since our test statistics lie in the range of critical values which means it doesn't lie in the rejection region, so we have sufficient evidence to accept null hypothesis.

Therefore, we conclude that the actual percentage that fail is same as the stated percentage and the manager's claim is not supported.

5 0
3 years ago
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