This section of the Engineering Statistics Handbook describes in detail the process of choosing an experimental design to obtain the results you need. The basic designs an engineer needs to know about are described in detail.
The GAISE project was funded by a Strategic Initiative Grant from ASA in 2003 to develop ASA-endorsed guidelines for assessment and instruction in statistics in the K-12 curriculum and for the introductory college statistics course.
A computer intensive introductory course for graduate students. A veritable online course with Powerpoint and Excel downloadable files for viewing. Also provides related outside links for further investigation on related topics.
This lesson on observational studies discusses the nature of such studies, the relationships between various data sets, and regression. Graphs illustrate the relationships, and exercises at the end test the user's comprehension and understanding. It is taken from the online textbook for West. Mich. Univ. online introductory stats course.
The function of this site is to collect, compile, analyse, abstract and publish statistical information relating to the commercial, industrial, financial, social, economic and general activities and condition of the people.
A good resource for problems in statistics in engineering. Contains some applets, and good textual examples related to engineering. Some topics include Monte Carlo method, Central Limit Theorem, Risk, Logistic Regression, Generalized Linear .Models, and Confidence.
This site provides the description and instructions for as well as the link to the Diffusion Limited Aggregation: Growing Fractal Structures applet. This applet strives to describe, classify, and measure different random fractal patterns in nature.
The user is be able to change the mean and the standard deviation using the sliders and see the density change graphically. The check buttons (68, 95, 99) will help one realize the appropriate percentages of the area under the curve. An example of thiis "68-95-99.7" rule follows.
This site provides the description and instructions for as well as the link to The Self-Avoiding Random Walk applet. In the SAW applet, random walks start on a square lattice and then are discarded as soon as they self-intersect. If a random walk survives after N steps, we compute the square of the distance from the origin, sum it up, and divide by the number of survivals. This variable is plotted on the vertical axis of the graph, which is plotted to the right of the field where random walks travel.