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. So 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. WE WILL GO OVER
CALCULATING THESE
STATISTICS IN LESSON 3.
The second way we could summarize this data is graphically by creating
a box plot or a histogram. This method would provide information on
the distribution of fuel loadings. WE WILL GO OVER HOW TO CREATE
THESE TYPES OF GRAPHICAL SUMMARIES AS WELL AS OTHERS IN LESSON 3.
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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