Mathematics, 29.07.2020 02:01 mrstealyogirl40

Suppose the sediment density (g/cm) of a randomly selected specimen from a certain region is normally distributed with mean 2.68 and standard deviation 0.92. A. If a random sample of 25 specimens is selected, what is theprobability that the sample average sediment density is at most3.00? Between 2.68 and 3.00
B. How large a sample size would be required to ensure thatthe first probability in part (a) is at least .99 ?

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Answer from: ashley24109

The sample size must be 45 large enough that would ensure that the first probability in part (a) is at least 0.99.

Step-by-step explanation:

We are given that the sediment density (g/cm) of a randomly selected specimen from a certain region is normally distributed with mean 2.68 and standard deviation 0.92.

Let $\bar X$ = sample average sediment density

The z-score probability distribution for the sample mean is given by;

Z = $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ ~ N(0,1)

where, $\mu$ = population mean = 2.68

$\sigma$ = population standard deviation = 0.92

n = sample of specimens = 25

(a) The probability that the sample average sediment density is at most 3.00 is given by = P( $\bar X$ $\leq$ 3.00)

P( $\bar X$ $\leq$ 3.00) = P( $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ $\leq$ $\frac{3.00-2.68}{\frac{0.92}{\sqrt{25} } }$ ) = P(Z $\leq$ 1.74) = 0.9591

The above probability is calculated by looking at the value of x = 1.74 in the z table which has an area of 0.9591.

Also, the probability that the sample average sediment density is between 2.68 and 3.00 is given by = P(2.68 < $\bar X$ < 3.00)

P(2.68 < $\bar X$ < 3.00) = P( $\bar X$ < 3.00) - P( $\bar X$ $\leq$ 2.68)

P( $\bar X$ < 3.00) = P( $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ < $\frac{3.00-2.68}{\frac{0.92}{\sqrt{25} } }$ ) = P(Z < 1.74) = 0.9591

P( $\bar X$ $\leq$ 2.68) = P( $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ $\leq$ $\frac{2.68-2.68}{\frac{0.92}{\sqrt{25} } }$ ) = P(Z $\leq$ 0) = 0.50

The above probability is calculated by looking at the value of x = 1.74 and x = 0 in the z table which has an area of 0.9591 and 0.50.

Therefore, P(2.68 < $\bar X$ < 3.00) = 0.9591 - 0.50 = 0.4591.

(b) Now, we have to find a sample size that would ensure that the first probability in part (a) is at least 0.99, that is;

P( $\bar X$ $\leq$ 3.00) $\geq$ 0.99

P( $\frac{\bar X-\mu}{\frac{\sigma}{\sqrt{n} } }$ $\leq$ $\frac{3.00-2.68}{\frac{0.92}{\sqrt{n} } }$ ) $\geq$ 0.99

P(Z $\leq$ $\frac{3.00-2.68}{\frac{0.92}{\sqrt{n} } }$ ) $\geq$ 0.99

Now, in the z table; the critical value of x which has an area of at least 0.99 is given by 2.3263, that is;

$\frac{3.00-2.68}{\frac{0.92}{\sqrt{n} } }=2.3263$

$\sqrt{n} } }=\frac{ 2.3263\times 0.92}{0.32}$

$\sqrt{n} } }=6.69$

n = 44.76 ≈ 45 {By squaring both sides}

Hence, the sample size must be 45 large enough that would ensure that the first probability in part (a) is at least 0.99.

Answer from: Quest

e^-kt = n/n0 = 0.79

-kt = ln 0.79

t = - ln 0.79/0.0001

= 2357 years

step-by-step explanation:

Answer from: Quest

hence, the required result is $b-a=\left[\begin{array}{ccc}1& 1& -2\\1& 1& -2\\1& 1& -2\end{array}\right]$

step-by-step explanation:

suppose we have two matrices a and b

we will assume the two matrices

$a=\left[\begin{array}{ccc}1& 2& 3\\4& 5& 6\\7& 8& 9\end{array}\right]$

$b=\left[\begin{array}{ccc}2& 3& 1\\5& 6& 4\\8& 9& 7\end{array}\right]$

we have to compute b-a which means subtracting corresponding elements of a from b.

$b=\left[\begin{array}{ccc}2& 3& 1\\5& 6& 4\\8& 9& 7\end{array}\right]$ - $a=\left[\begin{array}{ccc}1& 2& 3\\4& 5& 6\\7& 8& 9\end{array}\right]$

$b-a=\left[\begin{array}{ccc}1& 1& -2\\1& 1& -2\\1& 1& -2\end{array}\right]$

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