Stan takes 1.5 hours to paint one door.

Mathematics

1 answer:

12345 [234]3 years ago

5 0

Answer:

1.5(d)

Step-by-step explanation:

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Eighty students are going on a field trip.the total cost includes 2 bus rentals that cost 960 and 10$ per student for lunch. Wha

Westkost [7]

80 students.
2 bus rentals - $960.
$10 per student for lunch.

so we do $960 / 80 = which is $12.

so each student pays $12 for a bus rental + $10 for lunch so all together for the whole field trip it's $22.

6 0

3 years ago

Help please<br>6th Grade Math

Hitman42 [59]

Can I see the full problem from the worksheet?your work looks correct to me.

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3 years ago

The length of a rectangle is I yd more than double the width, and the area of the rectangle is 28 yd. Find the dimensions of the

tester [92]

Answer:

width = 7/2

length = 8

Step-by-step explanation:

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2 years ago

A process is producing a particular part where the thickness of the part is following a normal distribution with a µ = 50 mm and

Hitman42 [59]

Answer:

0.13% probability that this selected sample has an average thickness greater than 53

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 $s = \frac{\sigma}{\sqrt{n}}$ .