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3 years ago

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One employee earns a weekly salary of $428, and another works hourly,earning $15 per hour. How many hours does the hourly employ

ee need to work to make the same weekly earnings as the standard employee?

1 answer:

ElenaW [278]3 years ago

3 0

Answer:

B. 28.5

Step-by-step explanation:

Very simple. Just do 15 * 28.5 which will get you 427.5.

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-112/3 x (-4 1/5) =?

TEA [102]

Answer:

sorry Wala po akong answer ehhh sorry

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2 years ago

Sadie is saving for a new car. Below is the total amount of money in her savings account on the last day of each month. Show all

ICE Princess25 [194]

The mean is 10,724.28.

Explanation:

The mean is all of the values divided by the number of values there are.

So what you have to do is add all of the numbers and divide it by the amount of numbers there are.

10,150+10,211+10,424+10,769+10,884+11,155+11,477= 75,070.

Since there are 7 numbers, divide 75,070/7 and you get your mean, which is 10,724.28 rounded.

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1 year ago

Find the surface area of a pyramid

Cerrena [4.2K]

Answer:

$A=lw+l\sqrt{(\frac{1}{2}w) ^{2} +h^{2} } +w\sqrt{(\frac{1}{2}l) ^{2} +h^{2} }$

Step-by-step explanation:

The formula for the surface area of a pyramid is $A=lw+l\sqrt{(\frac{1}{2}w) ^{2} +h^{2} } +w\sqrt{(\frac{1}{2}l) ^{2} +h^{2} }$

7 0

3 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) $COV = 0.007255$

(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

Identify which statement about the mean of a discrete random variable is not true or state that they are all true.Choose the cor

pashok25 [27]

Answer:

A, C are true . B is not true.

Step-by-step explanation:

Mean of a discrete random variable can be interpreted as the average outcome if the experiment is repeated many times. Expected value or average of the distribution is analogous to mean of the distribution.

The mean can be found using summation from nothing to nothing x times Upper P (x) , i.e ∑x•P(x).

Example : If two outcomes 100 & 50 occur with probabilities 0.5 each. Expected value (Average) (Mean) : ∑x•P(x) = (0.5)(100) + (0.5)(50) = 50 + 25 = 75

The mean may not be a possible value of the random variable.

Example : Mean of possible no.s on a die = ( 1 + 2 + 3 + 4 + 5 + 6 ) / 6 = 21/6 = 3.5, which is not a possible value of the random variable 'no. on a die'

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3 years ago