PLZ HELP, AM BEING TIMED

AaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaA

Ganezh [65]

Answer:

the answer is

B.Plate

i hope this helps ~_~

4 0

3 years ago

Read 2 more answers

A case of deodorant costs $57. You get a business discount of 15%, and you have a coupon for 20% off. How much will the case of

finlep [7]

Answer:

$37.05

Step-by-step explanation:

If you take 15% and 20% you get (15%+20%) which is 35%, then you take 100%-35% you get 65%, 65% of 57 is 37.05.

Thus Your Answer: $37.05

4 0

3 years ago

HELPPP ASAP WILL MARK BRAINILEST

Alenkasestr [34]

Andy is correct! Andy has the function 4, his leading coefficient is negative, and his functions contains zeros. Hope this helps!

7 0

3 years ago

Thompson and Thompson is a steel bolts manufacturing company. Their current steel bolts have a mean diameter of 144 millimeters,

kkurt [141]

Answer:

0.0524 = 5.24% probability that the sample mean would differ from the population mean by more than 2 millimeters.

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 diameter of 144 millimeters, and a variance of 49.

This means that $\mu = 144, \sigma = \sqrt{49} = 7$

Sample of 46:

This means that $n = 46, s = \frac{7}{\sqrt{46}}$

Wat is the probability that the sample mean would differ from the population mean by more than 2 millimeters?

Above 144 + 2 = 146 or below 144 - 2 = 142. Since the normal distribution is symmetric, these probabilities are equal, which means that we find one of them and multiply by two.

Probability the sample mean is below 142:

p-value of Z when X = 142, so:

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

By the Central Limit Theorem

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