What is the value of y? Enter your answer in the box.

a worker at a mill is delivering 5lbs bags of flour to a local warehouse, each box holds 12 bags. If the warehouse orders 3 tons

ivolga24 [154]

I'm pretty sure that u multiply 12 and 5 and u get 60 and that's in only one box just 60lbs then u find how many pounds in a ton which is 2,000 then u have 3 tons so multiple 2,000 and 3 and u get 6,000 so then u divide 60 and 6,000 and u get 100 I'm pretty sure that's how u do it

8 0

3 years ago

Read 2 more answers

Please can someone help

Sergeu [11.5K]

Answer = £44,918

220x8.8 = 1936
2.3x2.1 = 4.83
1936 + 4.83 = 1940.83
1940.83/1.6 = 1213.01
1214x37 = 44918

6 0

2 years ago

A selective college would like to have an entering class of 950 students. Because not all students who are offered admission acc

pogonyaev

Answer:

a) The mean is 900 and the standard deviation is 15.

b) 100% probability that at least 800 students accept.

c) 0.05% probability that more than 950 will accept.

d) 94.84% probability that more than 950 will accept

Step-by-step explanation:

We use the normal approximation to the binomial to solve this question.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

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.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .