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Mamont248 [21]
3 years ago
6

(URGENT)Which summation formula represents the series below?

Mathematics
2 answers:
MrRissso [65]3 years ago
6 0

Answer:

Σ - 47 - 15

Step-by-step explanation:

Hope this helps!

sladkih [1.3K]3 years ago
4 0

Answer:

Σ-47-15)

Step-by-step explanation:

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H(1)=-6 h(2)= 20 h(n)= h(n-2)+h(n-1) What is the value of h(3)?
Elina [12.6K]

9514 1404 393

Answer:

  14

Step-by-step explanation:

Use the formula with n=3.

  h(3) = h(3-2) +h(3-1)

  h(3) = h(1) +h(2)

  h(3) = -6 +20 . . . . . substitute the given values

  h(3) = 14

6 0
3 years ago
The population of a city is 100,000. It doubles each decade for 5 decades. Select all
nikitadnepr [17]
Not sure but I think it’s C
5 0
2 years ago
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Using the following data, calculate the mean absolute deviation:
Bogdan [553]
First set of data:
Mean - 6.5
Absolute deviation - 2.4

Second set of data:
Mean - 4.475
Absolute deviation - 2.275
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3 years ago
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Expand the following.<br> (3x + 2)2<br> A.9x2+6x+4<br> B.9x2+4<br> C.3x2+4<br> E.9x2+12x+4
PolarNik [594]

Step-by-step explanation:

E

working ;

(3x+2)^2

*Apply Perfect Square Formula : (a+b) =a^2+2ab+b^2

a = 3x,b = 2

(3x)^2 + 3x.2+2^2

finally Answer is:

= 9x^2 + 12x +4

5 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
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