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2 years ago

What is the value if X 3x/7 - 11 = 16

Mathematics

1 answer:

slamgirl [31]2 years ago

6 0

Answer:

Step-by-step explanation:

hope that helped

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QUICK QUICK PLEASE! 1 MINUTE

Dima020 [189]

Step-by-step explanation:

Total tomato plants = 24 + 30 = 54

Total green bean plants = 18 + 25 = 43

The ratio of tomato plants to green bean plants

$= \frac{54}{43} = 54 \: : \: 43$

4 0

3 years ago

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Come here if you can solve this highly complicated question~ :0

Natasha2012 [34]

Yes mate,

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3 years ago

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Find the volume of the cone.

Contact [7]

<em>V</em>≈301.59

I think this is the answer.

Hope this helps!

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3 years ago

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Mila Hawkins purchased a bookshelf for $210.00.

Alenkinab [10]

Answer:

$12.60

Step-by-step explanation:

6% of 210 is .06 x 210 which equals 12.60

6 0

2 years ago

2. The quality assurance department inspects its production line. The product either fails or passes the inspection. Past experi

Oksana_A [137]

Answer:

(a) $E(X) = 950$

(b) $COV = 0.007255$

Step-by-step explanation:

The given problem can be solved using binomial distribution since the product either fails or passes, the probability of failure or success is fixed and there are n repeated trials.

probability of failure = q = 0.05

probability of success = p = 1 - 0.05 = 0.95

number of trials = n = 1000

(a) What is the expected number of non-defective units?

The expected number of non-defective units is given by

$E(X) = n \times p \\\\E(X) = 1000 \times 0.95 \\\\E(X) = 950$

(b) what is the COV of the number of non-defective units?

The coefficient of variance is given by

$COV = \frac{\sigma}{E(X)}$

Where the standard deviation is given by

$\sigma = \sqrt{n \times p\times q} \\\\\sigma = \sqrt{1000 \times 0.95\times 0.05} \\\\\sigma = 6.892$

So the coefficient of variance is

$COV = \frac{6.892}{950}$

$COV = 0.007255$

(c) What is the probability of having more than 980 non-defective units?

We can use the Normal distribution as an approximation to the Binomial distribution since n is quite large and so is p.

$P(X > 980) = 1 - P(X < 980)\\\\P(X > 980) = 1 - P(Z < \frac{x - \mu}{\sigma} )\\\\$

We need to consider the continuity correction factor whenever we use continuous probability distribution (Normal distribution) to approximate discrete probability distribution (Binomial distribution).

$P(X > 980) = 1 - P(Z < \frac{979.5 - 950}{6.892} )\\\\P(X > 980) = 1 - P(Z < \frac{29.5}{6.892} )\\\\P(X > 980) = 1 - P(Z < 4.28)\\\\$

The z-score corresponding to 4.28 is 0.99999

$P(X > 980) = 1 - 0.99999\\\\P(X > 980) = 0.00001\\\\$

So it means that it is very unlikely that there will be more than 980 non-defective units.

8 0

3 years ago