Find the rate of decay of the function b(x)=4(0.006)^x<br><br> Enter your answer as a percent

Please helppp, thank you

yulyashka [42]

My prediction would be 1,659 defective brakes. I hope this helps you

6 0

3 years ago

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Solve the inequality for b.<br><br>4b - 12 -5b < 9b + 8

ValentinkaMS [17]

Answer:

9b-12<9b+8

Step-by-step explanation:

b<20

8 0

3 years ago

Im so confused right now. how do I do this?

Sedbober [7]

Step-by-step explanation:

V= L×W×H
you only need to know one side to figure out the
volume of a cube
volume is in 3Dimensions
Multiple the sides in any order
which side you call length, width, or height doesn't matter

that's how you find the answer.

does that help?

6 0

2 years ago

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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) $COV = 0.007255$

(c) $P(X > 980) = 0.00001\\\\$

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

If you were to roll two dice, how many different ways could you roll double fours?

muminat

Answer:

There are 6 ways we can roll doubles out of a possible 36 rolls (6 x 6), for a probability of 6/36, or 1/6, on any roll of two fair dice. So you have a 16.7% probability of rolling doubles with 2 fair six-sided dice

Step-by-step explanation:

5 0

2 years ago

Find the rate of decay of the function b(x)=4(0.006)^x Enter your answer as a percent