STS 3250 Design and Analysis of Experiments

This course explores methods of designing, conducting, and analyzing scientific experiments to address research questions. Emphasis is placed on applications using real data as well as on the underlying mathematical structures and theory. Topics include completely randomized designs, randomized block designs, factorial treatment designs, split-plot designs, and analysis of covariance. Advanced statistical software will be used, and written reports will link statistical theory and practice with the communication of results.

Credits

4 sh

Prerequisite

STS 2120 or permission of the statistics program coordinator

Course Types

Advanced Studies

Offered

• Fall

Course Outcomes

1. Statistics promotes quantitative critical thinking skills that should serve the student in the rest of their course studies at Elon. Specific outcomes that should prove valuable include the ability to:
   * Develop defensible strategies for experimentation.
2. * Critically form, think about, and assess scientific questions.
3. * Identify the advantages and disadvantages of various experimental designs.
4. * Effectively organize and present data both visually and in writing.
5. * Write reproducible code and replicable protocols for experiments.
6. * Learn analytical techniques for interpreting data from various experimental designs.
7. * Use statistical software to obtain appropriate results
8. * Appropriately interpret the results of statistical inference methods.
9. * Develop sufficient statistical skills to critically examine other people’s research and carefully perform one’s own.