But the mean can be a misleading statistic. It only describes the average value and
thus provides no information on the distribution of the responses. Different patterns
of responses can produce the same mean score. Therefore, it is important to use the
standard deviation along with the frequency distribution to gain a clearer understanding
of the data. The frequency distribution is a graphical method for displaying data that
shows the number of times a particular response was given. For example, the data in
Table 7.3 suggest that both pay and praise from the supervisor are equally valued with
a mean of 4.0. However, the standard deviations for these two measures are very different
at 0.71 and 1.55, respectively. Table 7.4 shows the frequency distributions of
the responses to the questions about pay and praise from the supervisor. Employees’
responses to the value of pay are distributed toward the higher end of the scale, with
no one rating it of low or very low value. In contrast, responses about the value of
praise from the supervisor fall into two distinct groupings: Twenty-five employees felt
that supervisor praise has a low or very low value, whereas 75 people rated it high or
very high. Although both rewards have the same mean value, their standard deviations
and frequency distributions suggest different interpretations of the data