PLEASE HELP ASAP!!! BRAINLIEST FOR BEST ANSWER

Mathematics

2 answers:

GalinKa [24]4 years ago

7 0

It is A-------------------

MatroZZZ [7]4 years ago

3 0

The answer is A. :))

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Shanghai Company sells glasses, fine china, and everyday dinnerware. It uses activity-based costing to determine the cost of the

Kay [80]

Answer:

glasses 13 times 2 =26 China 13times4=52 dinnerware 13 times 6= 78 fine China 5100 times 4 pounds =20400 pounds times 13 a pound =265200.

7 0

4 years ago

Need a little bit of help here

marusya05 [52]

Hi there,

If what you are trying to find is the volume, then:

Here's the equation:

4×6×2 = 48 --- volume of the smaller rectangular box
12×14×2 = 336 --- volume of the bigger box
48 + 336 = 384 --- the total volume of the figure

Hope this helped :P

3 0

4 years ago

Read 2 more answers

Ask Your Teacher The level of nitrogen oxides (NOX) in the exhaust after 50,000 miles or fewer of driving of cars of a particula

Georgia [21]

Answer:

The level is L = 0.084

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 normally distributed samples can be solved using 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 sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$