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Nitella [24]
3 years ago
14

1/3×24 to the power of 2 times 30

Mathematics
1 answer:
svp [43]3 years ago
4 0
1/3*(24^2)*30=5760

Any questions just ask. Thanks
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Mary's age is 10 years less than 2 times Joe's age. If the difference between their ages is 30, how old is Mary?
zheka24 [161]

Answer:

its 5

Step-by-step explanation:

cause 2 divided by 30is 15 minus 10 its 5

4 0
3 years ago
Read 2 more answers
PLEASE ANSWER TODAY<br><br><br> Express a 10/3 b 7/3 in simplified radical form.
34kurt
I guess this is what you mean     3√a^10      and 3√b^7
4 0
3 years ago
Problem page a light bulb consumes 2400 watt-hours per day. how many watt-hours does it consume in 3 days and 6 hours?
Volgvan
Calculate for 3 days: 2,400 x 3 = 7,200

Calculate 1 day per hour: 2,400 ÷ 24 = 100
Calculate for 6 hours: 100 x 6 = 600

7,200 + 600 = 7,800 watt-hours
8 0
3 years ago
What are the factors of 37, 51, and 45? i just dont get it
lbvjy [14]
37 is prime, so it's only factors are 1 and 37 
<span>51 has factors of 1,51 and 3,17 </span>
<span>45 has factors of 1,45 ; 3,15 and 5,9 </span>
5 0
3 years ago
Is the confidence interval affected by the fact that the data appear to be from a population that is not normally​ distributed?
sp2606 [1]

Answer:

D. No, because the sample size is large enough.

Step-by-step explanation:

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".

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".

If the sample size is higher than 30, on this case the answer would be:

D. No, because the sample size is large enough.

And the reason is given by The Central Limit Theorem since states if the individual distribution is normal then the sampling distribution for the sample mean is also normal.

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}})

If the sample size it's not large enough n<30, on that case the distribution would be not normal.

7 0
3 years ago
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