Introduction to a variety of useful statistical ideas and techniques - Improving the User Experience through Practical Data Analytics - page 17

FIGURE 1.12
Getting speciic in using Data Analysis to ind a conidence interval.
We now get out output (our answer!) by just clicking on OK (see bent arrow in
Figure 1.12 ). Drum roll please! See Figure 1.13 .
The output has a lot of information. However, to ind the conidence interval,
only the irst value (“Mean”—in row 3, column B) and last value (conidence level
(95%)—row 16, column B). The irst value is X-bar (as we know, this is the center
of our conidence interval), and the last value (row 16) is “e” the amount we add and
subtract to X-bar (with the accompanying note that it, indeed, is a 95% conidence
interval). So, our conidence interval is calculated by some basic arithmetic:
4.333−0.414 to 4.333+0.414
or
3 . 92 −−−−−−−−−−−−−−−−−4 . 75 .
Thus, we can be 95% conident that the interval, 3.92-4.75, contains the true
mean satisfaction with the design ; in looser terms that may sound more satisfactory
to many people, “We have 95% conidence that the true mean satisfaction is between
3.92 and 4.75.”