At Stop n Shop they are selling fried chicken for $1.95 a pound. If Amiyah buys 13.2 pounds how much will she spend?

A company that makes boxes finds that 6 out of 8 boxes are damaged.What percent of the boxes are damage?

Elanso [62]

8 boxes is 100%, 6 out of 8 is 6/8 x 100% = 75%

7 0

3 years ago

There are 40 runners in a race. How many ways can the runners finish first, second, and third?

k0ka [10]

Answer:

117600

Step-by-step explanation:

50 x 49 x 48 = 117,600 ways

You have 50 possible for 1st, 49 for 2nd, 48 for 3rd

or

Permutations 50P3 = 117,600

5 0

3 years ago

The amount people pay for cable service varies quite a bit but the mean monthly fee is $142 and the standard deviation is $29. t

zhuklara [117]

Answer:

a) By the Central Limit Theorem, the mean is $142 and the standard deviation is $0.7488.

b) By the Central Limit Theorem, approximately normal.

c) 0.0901 = 9.01% probability that the average cable service paid by the sample of cable service customers will exceed $143

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .