Please answer correctly !!!!!!!!!!!! Will mark brainliest !!!!!!!!!!!

Express the following

krok68 [10]

Answer:

1. 32

2. 24

3. $\frac{1}{12}$

4. $\frac{1}{8}$

5. 15

6. $\frac{1}{15}$

Step-by-step explanation:

1. 4÷ $\frac{1}{8} = 4*8=32$

2. 6÷ $\frac{1}{4} = 6*4=24$

3. $\frac{1}{3}$ ÷4= $\frac{1}{3}*\frac{1}{4} =\frac{1}{12}$

4. $\frac{1}{2}$ ÷4= $\frac{1}{2} *\frac{1}{4} =\frac{1}{8}$

5. 5÷ $\frac{1}{3} =5*3=15$

6. $\frac{1}3}$ ÷5= $\frac{1}{3} *\frac{1}{5} = \frac{1}{15}$

3 0

3 years ago

The average amount of water in randomly selected 16-ounce bottles of water is 16.15 ounces with a standard deviation of 0.45 oun

vekshin1

Answer:

0.0179 = 1.79% probability that the mean of this sample is less than 15.99 ounces of water.

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