-[-8+7]-[1-7] what does it equal show work

HELP ME PLEASE I really don’t know what to do lol

Leya [2.2K]

The answer

272/32 = 8.5 hrs

7 0

3 years ago

The value of y varies directly with x. When y = 75, x = ½ . What is the value of y when x is 2 ¼ ? A. 168.75 C. 66.67 B. 16.67 D

lora16 [44]

Answer:

Step-by-step explanation:

The value of y varies directly with x. When y = 75, x = ½ . What is the value of y when x is 2 ¼ ? A. 168.75 C. 66.67 B. 16.67 D. 337.5

y ∝x

y = kx

k = y/x

8 0

2 years ago

A system has two failure modes. One failure mode, due to external conditions, has a constant failure rate of 0.07 failures per y

nadya68 [22]

Answer:

0.9177

Step-by-step explanation:

let us first represent the two failure modes with respect to time as follows

R₁(t) for external conditions

R₂(t) for wear out condition ( Wiebull )

Now,

$R1(t) = e^{-nt} .....1$

where t = time in years = 1,

n = failure rate constant = 0.07

Also,

$R2(t)=e^{-(\frac{t}{Q} )^{B} }......2$

where t = time in years = 1

where Q = characteristic life in years = 10

and B = the shape parameter = 1.8

Substituting values into equation 1

$R1(t) = e^{-(0.07)(1)} \\\\R1(t) = e^{-0.07}$

Substituting values into equation 2

$R2(t)=e^{-(\frac{1}{10} )^{1.8} }\\\\R2(t)=e^{-(0.1)}^{1.8} }\\\\R2(t)=e^{-0.0158}$

let the <em>system reliability </em>for a design life of one year be Rs(t)

hence,

Rs(t) = R1(t) * R2(t)

t = 1

$Rs(1) = [e^{-0.07} ] * [e^{-0.0158} ] = 0.917713$

Rs(1) = 0.9177 (approx to four decimal places)

5 0

3 years ago

Select the correct answer.

andrew-mc [135]

I think the answer would be 8+9

4 0

3 years ago

a) A large hotel in Miami has 900 rooms (all rooms are equivalent). During Christmas, the hotel is usually fully booked. However

Olegator [25]

Answer:

14.69% probability that this happens

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes 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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$