The distribution of actual weights of 8-ounce wedges of cheddar cheese produced at a dairy is normal with mean 8.1 ounces and standard deviation 0.2 ounces. a sample of 10 of these cheese wedges is selected. the distribution of the sample mean of the weights of cheese wedges is:

approximately normal, mean 8.1, standard deviation 0.2.

approximately normal, mean 8.1, standard deviation 0.020.

it is not possible to tell because the sample size is too small.

approximately normal, mean 8.1, standard deviation 0.063.

approximately Normal, mean 8.1, standard deviation 0.063.

Step-by-step explanation:

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".  

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

Let X the random variable weights of 8-ounce wedges of cheddar cheese produced at a dairy. We know from the problem that the distribution for the random variable X is given by:

We take a sample of n=10 . That represent the sample size.

What can we say about the shape of the distribution of the sample mean?

From the central limit theorem we know that the distribution for the sample mean is also normal and is given by:

approximately Normal, mean 8.1, standard deviation 0.063.

answer:

it will cost 480 dollars to refurbish the larger wood floor

step-by-step explanation:

as it's a ratio of 4 that costs 384 dollars, divide the price by the ratio

384 / 4 = 96 dollars

96 dollars per unit of the ratio

now to get the price to refurbish the larger wood floor, times the price by the units

96 * 5 = 480

50- 250 is correct i did that one too

step-by-step explanation: