© John Wiley & Sons, Inc.

FIGURE 9-5: Population distribution of systolic blood pressure (SBP) measurements in mmHg (a) and distribution of a sample

from that population (b).

The smooth curve in Figure 9-5a shows how SBP values are distributed in an infinitely large

population. The height of the curve at any SBP value is proportional to the fraction of the population in

the immediate vicinity of that SBP. This curve has the typical bell shape of a normal distribution.

The histogram in Figure 9-5b indicates how the SBP measurements of 60 study participants randomly

sampled from the population might be distributed. Each bar represents an interval or class of SBP

values with a width of ten mmHg. The height of each bar is proportional to the number of participants

in the sample whose SBP fell within that class.

Log-normal distributions

Because a sample is only an imperfect representation the population, determining the precise shape of

a distribution can be difficult unless your sample size is very large. Nevertheless, a histogram usually

helps you spot skewed data, as shown in Figure 9-6a. This kind of shape is typical of a log-normal

distribution (Chapter 25), which is a distribution you often see when analyzing biological

measurements, such as lab values. It’s called log-normal because if you take a logarithm (of any type)

of each data value, the resulting logs will have a normal distribution, as shown in Figure 9-6b.

© John Wiley & Sons, Inc.

FIGURE 9-6: Log-normal data are skewed (a), but the logarithms are normally distributed (b).