Microsoft Office Tutorials and References

In Depth Information

**Using NORM. DIST and POISSON. DIST to Determine Probabilities**

Figure 11-7 shows an example of using the GROWTH function to forecast

exponential data. Columns A and B contain the known data, and the range

D10:D19 contains the X values for which predictions are desired. The

GROWTH array formula was entered in E10:E19. The chart shows a

scatter plot of the actual data, up to X = 40, and the projected data, for X values

above 40. You can see how the projected data continues the exponential

curves that are fit by the actual data.

Figure 11-7:

Demonstrating

use of the

GROWTH

function

to project

exponential

data.

Using NORM.DIST and POISSON.DIST

to Determine Probabilities

You can get a good introduction to the normal distribution in Chapter 9. To

recap briefly, a normal distribution is characterized by its
mean
(the value

in the middle of the distribution) and by its
standard deviation
(the extent to

which values spread out on either side of the mean). The normal

distribution is a continuous distribution, which means that X values can be fractional

and aren’t restricted to integers. The normal distribution has a lot of uses

because so many processes, both natural and human, follow it.

NORM.DIST

The word
normal
in this context doesn’t mean “good” or “okay,” and a

distribution that is not normal is not flawed in some way. Normal is used simply to

mean “typical” or “common.”