The objective of descriptive statistics is to produce numbers which
describe attributes of the sample. In short, descriptive statistics
allows us to summarize our data in clear and meaningful way.
Example
Let’s assume we collected fuel loading data from 50
stands on a National Forest. We can now summarize this data in
one of two ways. First, we can summarize the data numerically by
computing statistics such as the mean and standard deviation; to
show the average amount of fuel loading and the degree to which fuel
loading differs between stands.
The second way we could summarize this data is graphically by
creating a stem and leaf diagram or a histogram. This method would
provide information on the distribution of fuel loadings.
You should remember that graphical representation of data is best
used to show patterns within the data; where as numerical
summarization is more precise and objective. However since both
types of summarization are complementary it is best to use both.
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