Evidence-Based Practice for Nurses

Do you have a professor who uses means and standard deviations, known as norm referencing,

for grading exams? What are the advantages to using this approach as opposed to straight

scales for grading? What are some disadvantages? Why would it be false to assume that having

more questions on exams would be advantageous to students when norm referencing is used?

CRITICAL THINKING EXERCISE 13-2

Using the coefficient of variation shows that age is more variable than salaries

among this group of nurses.

Tailedness: The Rule of 68–95–99.7

The concept of tailedness is important to understand when reading statistical

reports. Recall that a normal distribution is one in which the mean, median,

and mode are all equal and the data are symmetrical. In discussing tailedness,

the graph of a normal distribution is depicted as a bell-shaped curve, centered

about the mean (x), with three standard deviations marked to the right (posi-

tive) and also to the left (negative) (see Figure 13-7). Normal distributions

are not shown beyond three standard deviations in either direction because

approximately 99.7% of the data will lie within this range. Approximately 68%

of all data in a normal curve lie within one standard deviation of the mean,

and 95% of the data lie within two standard deviations of the mean. Thus, the

Rule of 68–95–99.7 tells us that for every sample, 99.7% of the data will fall

within three standard deviations of the mean. In Figure 13-8, note the sym-

metry about the mean for the standard deviations as they are divided in half

for each distribution percentage. For example, one standard deviation contains

–3 SD –2 SD –1 SD x– +1 SD +2 SD +3 SD

FIGURE 13-7

Normal Distribution with Standard

Deviations

KEY TERMS

tailedness: The

degree to which a

tail in a distribution

is pulled to the left

or to the right

Rule of 68–95–99.7:

Rule stating that

for every sample

68% of the data

will fall within one

standard deviation

of the mean; 95%

will fall within two

standard deviations;

99.7% of the data

will fall within three

standard deviations

348 CHAPTER 13 What Do the Quantitative Data Mean?