You measure the weights of a random sample of 400 male workers in the automotive industry. the sample mean is = 176.2 lbs. suppose that the weights of male workers in the automotive industry follow a normal distribution with unknown mean μ and standard deviation σ = 11.1 lbs. a 95% confidence interval for μ is:

A 95% confidence interval for μ is (175.287 lbs, 177.113 lbs).

Step-by-step explanation:

By the Central Limit Theorem, the mean of the sample is the same as the mean of the population. So:

Building the confidence interval:

We have that to find our level, that is the subtraction of 1 by the confidence interval divided by 2. So:

Now, we have to find z in the Ztable as such z has a pvalue of .

So it is z with a pvalue of , so

Now, find M as such

In which is the standard deviation of the population and n is the length of the sample. So

The lower end of the interval is the mean subtracted by M. So it is 176.2 - 0.9130 = 175.287 lbs

The upper end of the interval is the mean added to M. So it is 176.2 + 0.9130 = 177.113 lbs.

A 95% confidence interval for μ is (175.287 lbs, 177.113 lbs).

I believe the answer is: Prices for goods and services increased, and a dollar bought less than it previously had

In the 1970s, united states was experiencing a period of economic stagnation which later known as called the great inflation of the 1970s.

During this period, the number of unemployment skyrocketed and the value of our currency fall dramatically, which caused an increase in overall products and less amount of products it can obtain with previously same amount.