There are three main subdivisions within statistics: **efficient
summarization, tabulation and graphical display of data**; **design of
experiments**; and **statistical inference**. Data summarization was
historically the first major statistical activity. Experimental
design is of crucial importance before data are collected. However,
it is statistical inference which has seen most research and
practical application in recent years, and it is **inference** which
forms the direction of this course.
There are three main types of inference, namely point **estimation**,
**interval estimation** and **hypothesis testing**. In point estimation, for
each unknown parameter of interest a single value is computed from
the data, and used as an estimate of that parameter.
Instead of producing a single estimate of a parameter, interval
estimation provides a range of values which have a predetermined high
probability of including the true, but unknown, value of the
parameter.
**Hypothesis testing** sets up specific hypotheses regarding the
parameters of interest and assesses the plausibility of any specified
hypothesis by seeing whether the observed data support or refute that
hypothesis. Although hypothesis testing can often be artificial in the
sense that none of the proposed hypotheses will be exactly correct
(for example, exact equality of p for two species of birds is
unlikely), it is often a convenient way to proceed and underlies a
substantial part of scientific research.

The statistical community has during the last 10 years experienced a significant transformation stimulated by the technological developments in statistical computing environments, theoretical developments in stochastic based inference and simulation.

Students will learn how to use statistical software to facilitate the understanding of the foundations of multivariate analysis. Statistical packages will include SAS, S-Plus, and MatLab.

- S-Plus Guide (Postscript)
- S-Plus Notes 1 (Postscript)
- S-Plus Notes 2 (Postscript)
- S-Plus Notes 3 (Postscript)
- A shorter introduction to S-Plus aimed at regression.
- An Introduction to R.
### Helpful Statistics Sites

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**Author:***Calvin L. Williams, Mathematical Sciences-Clemson University, Clemson University*

**Last updated:***August 23, 2001*

**Send Comments to :***calvinw@ces.clemson.edu*