Answer:
The 95% confidence interval for the percent of all coffee drinkers who would say they are addicted to coffee is between 21% and 31%.
Step-by-step explanation:
In a sample with a number n of people surveyed with a probability of a success of
, and a confidence level of
, we have the following confidence interval of proportions.

In which
z is the zscore that has a pvalue of
.
The margin of error is:

A confidence interval has two bounds, the lower and the upper
Lower bound:

Upper bound:

In this problem, we have that:

Lower bound:

Upper bound:

The 95% confidence interval for the percent of all coffee drinkers who would say they are addicted to coffee is between 21% and 31%.
Answer:
30minutes
Step-by-step explanation:
I'm not totally positive, but if 9 minutes is 30% or 3/10 of his time, then
10% or 1/10 is 3 minutes. So 100% or 10/10 is 30 minutes.
Answer:
The sample standard deviation is 15.3.
Step-by-step explanation:
Given data items,
84, 85, 83, 63, 61, 100, 98,
Number of data items, N = 7,
Let x represents the data item,
Mean of the data points,


Hence, sample standard deviation would be,






<span>So L = x-4, W = x-4, H = x
Volume = length * width * height
V = L * W * H
V = (x-4)*(x-4)*x
V = ???
</span>x is the height, so x-4 is the length and also the width since <span>length and a width of 4in. less than the height</span>
Answer:
Power analysis
Step-by-step explanation:
Power analysis is a significant part of test structure. It permits us to decide the example size required to recognize an impact of a given size with a given level of certainty. On the other hand, it permits us to decide the likelihood of recognizing an impact of a given size with a given degree of certainty, under example size requirements. On the off chance that the likelihood is unsuitably low, we would be shrewd to adjust or forsake the analysis.
The principle reason underlying power analysis is to assist the analyst with determining the littlest example size that is appropriate to recognize the impact of a given test at the ideal degree of hugeness.