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bulgar [2K]
3 years ago
8

Pivot the system about the element in row 2, column 1. (Enter the augmented matrix with all cells in their original position.)

Mathematics
1 answer:
Crazy boy [7]3 years ago
4 0

Answer:

Step-by-step explanation:

pivoting means producing a unit column in  matrices.

The aim is to make the elements above and below the pivot element o.

so we have;

\left[\begin{array}{cccc}1&2&4&3\\2&8&6&4\\-1&4&2&3\end{array}\right]

we will make the pivot element a unit element that is 1.

\frac{1}{2}R_{2}  → \left[\begin{array}{cccc}1&2&4&3\\1&4&3&2\\-1&4&2&3\end{array}\right]

next we perform the operation R_{1} - R_{2} then we have

\left[\begin{array}{cccc}0&-2&1&1\\1&4&3&2\\-1&4&2&3\end{array}\right]

next we also perform the operation R_{3} + R_{2} thus we have

\left[\begin{array}{cccc}0&-2&1&1\\1&4&3&2\\0&8&5&5\end{array}\right]

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15

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To get 10 percent, you divide by 10.

150 divided by 10 equals 15.

3 0
3 years ago
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The mean height of women in a country (ages 20-29) is 64 4 inches A random sample of 50 women in this age group is selected What
Simora [160]

Answer:

0.0721 = 7.21% probability that the mean height for the sample is greater than 65 inches.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 64.4 inches, standard deviation of 2.91

This means that \mu = 64.4, \sigma = 2.91

Sample of 50 women

This means that n = 50, s = \frac{2.91}{\sqrt{50}}

What is the probability that the mean height for the sample is greater than 65 inches?

This is 1 subtracted by the p-value of Z when X = 65. So

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{65 - 64.4}{\frac{2.91}{\sqrt{50}}}

Z = 1.46

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1 - 0.9279 = 0.0721

0.0721 = 7.21% probability that the mean height for the sample is greater than 65 inches.

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If the range of f (x) = StartRoot m x EndRoot and the range of g (x) = m StartRoot x EndRoot are the same, which statement is tr
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Answer:

M IS M

Step-by-step explanation:

4 0
2 years ago
VERY VERY URGENT!!!!!!!
Arte-miy333 [17]

The answer is 7/25, because cos is opposite/hypothenuse.

3 0
3 years ago
SOLVE ANY BUT PUT THE NUMBER WITH IT
zubka84 [21]
1.
k = 1
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J = 12

k = 1 + 2 = 3
J = 7(3) + 5
J = 26

26 - 12 = 14
J increases by 14.


2. 
1/6 = 0.16 false (1/6 = 1.67)
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0.25 = 1/4 true (0.25 = 25/100 = 1/4)
<span>1/3 = 0.3 true (if rounded)</span>
<span>

3.
12 candles in 3 hours
12 </span>÷ 3 = 4
4 candles in 1 hour
4 × 8 = 32
32 candles in 8 hours


4.
$3.45 for 64 ounces
3.45 ÷ 64 = 0.05
$0.05 or 5 cents per ounce


5.
75 is what percent of 250?
75 ÷ 250 = 0.3
0.3 × 100 = 30
30%
8 0
3 years ago
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