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2 years ago

Which equation is equivalent to the formula m = ca? a = cm a equals m over c c = am c equals a over m.

Mathematics

2 answers:

disa [49]2 years ago

8 0

The option b which is $a=\dfrac{m}{c}$ is correct answer.

Given to us:

$m=ca$

dividing both sides by c, we get

$m=ca\\\\\dfrac{m}{c}=\dfrac{ca}{c}$

canceling c from right hand side, we get

$\dfrac{m}{c}=a \\\\a=\dfrac{m}{c}$

Therefore, the option b which is $a=\dfrac{m}{c}$ is correct answer.

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Svet_ta [14]2 years ago

6 0

Answer:

a = m/c

Step-by-step explanation:

I translated the paragraph into these options. Please check accuracy.

m = ca?

a = cm No, a = m/c

a = m/c Yes

c = am No, c = m/a

c = a/m No, c = m/a

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Define z_alpha to be a z-score with an area of alpha to the right. For Example: z_0.10 means P(Z > z_0.10) = 0.10. We would a

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a) P(-z_0.025 < Z < z_0.025)

For this case we want a quantile that accumulates 0.025 of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(0.025,0,1)"

And for this case the two values are : $z_{crit}= \pm 1.96$

b) P(-z_{\alpha/2} < Z < z_{\alpha/2})

For this case we want a quantile that accumulates $\alpha/2$ of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(alpha/2,0,1)"

c) For this case we want to find a value of z that satisfy:

P(Z > z_alpha) = 0.05.

And we can use the following excel code:

"=NORM.INV(0.95,0,1)"

And we got $z_{\alpha/2}=1.64$

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

Part a

P(-z_0.025 < Z < z_0.025)

For this case we want a quantile that accumulates 0.025 of the area on the tails of the normal standard distribution, and for this case we can calculate the z value with the following excel codes:

"=NORM.INV(0.025,0,1)"

And for this case the two values are : $z_{crit}= \pm 1.96$

Part b

P(-z_{\alpha/2} < Z < z_{\alpha/2})

"=NORM.INV(alpha/2,0,1)"

Part c

For this case we want to find a value of z that satisfy:

P(Z > z_alpha) = 0.05.

And we can use the following excel code:

"=NORM.INV(0.95,0,1)"

And we got $z_{\alpha/2}=1.64$

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4 years ago

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marusya05 [52]

Answer:

I think either A or B. not sure though

Step-by-step explanation:

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3 years ago