Evidence-Based Practice for Nurses

Researchers ask the same types of questions when they analyze data using

inferential statistics. They ask, “What is the probability that the findings were a

result of chance?” Probability is the likelihood of the frequency of an event in

repeated trials under similar conditions. Probability is the percentage of times

that an event (e.g., “heads”) is likely to occur by chance alone. Probability is

affected by the concept of sampling error. Sampling error is the tendency for

statistical results to fluctuate from one sample to another. There is always a

possibility of errors in sampling, even when the samples are randomly selected.

The characteristics of any given sample are usually different from those of the

population. For example, suppose a fair coin was tossed 10 times for 10 dif-

ferent trials. A tally of the results in Table 13-9 shows that the trials varied;

but as expected, more of the trials were nearer 50% heads than 100% heads.

Trial 1 Trial 2 Trial 3 Trial 4 Trial 5 Trial 6 Trial 7 Trial 8 Trial 9 Trial 10

0 Heads

10 Tails

1 Head

9 Tails

2 Heads

8 Tails

X

3 Heads

7 Tails

4 Heads

6 Tails

X X

5 Heads

5 Tails

X X X

6 Heads

4 Tails

X X

7 Heads

3 Tails

X

8 Heads

2 Tails

X

9 Heads

1 Tail

10

Heads

0 Tails

TABLE 13-9 Coin Toss Example

KEY TERMS

probability:

Likelihood or

chance that an

event will occur in

a situation

sampling error:

Error resulting

when elements

in the sample do

not adequately

represent the

population

354 CHAPTER 13 What Do the Quantitative Data Mean?