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ipn [44]
2 years ago
8

Two fair dice are rolled. The score is the difference between the two dice.

Mathematics
1 answer:
yuradex [85]2 years ago
8 0

Answer:

What a question bro or sis

Step-by-step explanation:

where is the table

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Novay_Z [31]

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The simplest equation for a parabola is y = x^2

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3 years ago
23 and 24 I need help please
Gnoma [55]

Answer:

They should purchase the snack with the purple box. This is the answer for 23, i don't know what 24 is sorry.

Step-by-step explanation:

24÷3=8

8×5=40

so the first snacks would cost them $40.

then:

24÷4=6

6×6=36

so the second snacks would cost them $36

5 0
3 years ago
Is it okay to eat 8 day used by bread that been left in the refrigherater
FrozenT [24]

Bread is usually fine to eat if you don't see any mold.

Once refrigerated, it will retain its freshness for three to four days before becoming stale. If you want to extend its shelf life, packaged bread will stay fresh for at least three months in the freezer. If you do see mold, however, throw the bread out.

8 0
2 years ago
An accounting firm is planning for the next tax preparation season. From last years returns, the firm collects a systematic rand
Elena L [17]

Answer:

a)From the central limit theorem we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

And the standard error for the mean would be:

\sigma_{\bar X}= \frac{140}{\sqrt{100}} =14

b) We want this probability:

P(\bar X >120)

And we can use the z score formula given by:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And replacing we got:

z = \frac{120-90}{\frac{140}{\sqrt{100}}}= 2.143

And we can find this probability with the complement rule and the normal standard deviation or excel and we got:

P( z>2.143) = 1-P(Z

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 central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Solution to the problem

Part a

From the central limit theorem we know that the distribution for the sample mean \bar X is given by:

\bar X \sim N(\mu, \frac{\sigma}{\sqrt{n}})

And the standard error for the mean would be:

\sigma_{\bar X}= \frac{140}{\sqrt{100}} =14

Part b

We want this probability:

P(\bar X >120)

And we can use the z score formula given by:

z = \frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

And replacing we got:

z = \frac{120-90}{\frac{140}{\sqrt{100}}}= 2.143

And we can find this probability with the complement rule and the normal standard deviation or excel and we got:

P( z>2.143) = 1-P(Z

4 0
3 years ago
Solve for x in the equation (x + 7) (x minus 9) = 25
Artist 52 [7]

Answer:

10.43398113

Step-by-step explanation:

decimal for

3 0
2 years ago
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