Witch is grater 18/24 or 55%

Mathematics

1 answer:

GrogVix [38]3 years ago

6 0

Answer:

i would say 18/24

Step-by-step explanation:

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Each can of paint will cover 450 tiles. Augustin is painting 300 tiles in his bathroom,675 in his kitchen and 100 in his hallway

torisob [31]

Answer: 3 cans

Steps:
300 tiles + 675 tiles + 100 tiles = 1075 tiles

1075/450 tiles = 2.39

Cans aren’t sold in decimals so you will need to round 2.39 up to 3 cans.

8 0

4 years ago

the base of a parallelogram is 8 inches longer than twice the height. the area of the parallelogram is 64 square inches. what is

Yakvenalex [24]

$a = b \times h$

$64in^{2} = 16 \times 4$

where 16 is the base and 4 is the height.

16 - 8 is 8, and half of 8 is 4. So the height of the parallelogram is 4 inches.

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4 years ago

Can you help !!!!!! i’m doing a test

Flura [38]

Answer:

C. 16

Step-by-step explanation:

all you need to do is divide 8 by 1/2 which is 0.5

so, 8 divided by 0.5 = 16

good luck, hope this helps :)

4 0

3 years ago

An HP laser printer is advertised to print text documents at a speed of 18 ppm (pages per minute). The manufacturer tells you th

anastassius [24]

Answer:

0.288

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 are 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 sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .