Jonathan Stallings's guest appearances

Jonathan Stallings

LISA: Laboratory for Interdisciplinary Statistical Analysis - Short Courses

ERIC SMITH

Matt Williams

Anne Ryan

Block Design

Qing Li

Eric Vance

Khaled Bedair

Yiming Peng

Mark Seiss

Chris Franck

Nels Johnson

Marcos Carzolio

Liang Shan

Wandi Huang

Sai Wang

OwlTail

Across all disciplines, the ability to test theories by experimentation is vital for validation and discovery.  When designing an experiment, the researcher hopes to maximize the obtained information by reducing wasted resources and allocating treatments in such a way as to minimize variances.  Ideally, a design will account for major sources of variation so that the researcher can be confident the effects of treatments are not confounded with extraneous factors.  In this course, the basic principles of experimental design will be given and specific designs discussed.  The first designs introduced will be completely randomized designs, the most straightforward design when a researcher wants to test for differences among multiple treatments.  Optimal blocking strategies will then be presented as a variance-reducing technique, e.g. perhaps the researcher feels a subject's gender may significantly affect observations.  For each design we will discuss implementation, appropriate analysis and provide examples in SAS.  If time permits we may also introduce more complicated designs tailored specifically to the researchers attending the course.Course files available here: www.lisa.stat.vt.edu/?q=node/3374.

Across all disciplines, the ability to test theories by experimentation is vital for validation and discovery.  When designing an experiment, the researcher hopes to maximize the obtained information by reducing wasted resources and allocating treatments in such a way as to minimize variances.  Ideally, a design will account for major sources of variation so that the researcher can be confident the effects of treatments are not confounded with extraneous factors.  In this course, the basic principles of experimental design will be given and specific designs discussed.  The first designs introduced will be completely randomized designs, the most straightforward design when a researcher wants to test for differences among multiple treatments.  Optimal blocking strategies will then be presented as a variance-reducing technique, e.g. perhaps the researcher feels a subject's gender may significantly affect observations.  For each design we will discuss implementation, appropriate analysis and provide examples in SAS.  If time permits we may also introduce more complicated designs tailored specifically to the researchers attending the course.<br><br>Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/3374" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/3374</a>.

Designing Expierments and Collecting Useful Data by Jonathan Stallings

Across all disciplines, the ability to test theories by experimentation is vital for validation and discovery.  When designing an experiment, the researcher hopes to maximize the obtained information by reducing wasted resources and allocating treatments in such a way as to minimize variances.  Ideally, a design will account for major sources of variation so that the researcher can be confident the effects of treatments are not confounded with some extraneous factor.  In this course, the basic principles of experimental design will be given and specific designs discussed.  The first designs introduced will be completely randomized designs, the most straightforward design when a researcher wants to test for differences amongst multiple treatments.  Optimal blocking strategies will then be presented as a variance-reducing technique, e.g. perhaps the researcher feels a subject's gender may significantly affect observations.  For each design we will discuss implementation, appropriate analysis and provide examples in SAS.  If time permits we may also introduce more complicated designs tailored specifically to the researchers attending the course.Course files available here: www.lisa.stat.vt.edu/?q=node/2804.

Across all disciplines, the ability to test theories by experimentation is vital for validation and discovery.  When designing an experiment, the researcher hopes to maximize the obtained information by reducing wasted resources and allocating treatments in such a way as to minimize variances.  Ideally, a design will account for major sources of variation so that the researcher can be confident the effects of treatments are not confounded with some extraneous factor.  In this course, the basic principles of experimental design will be given and specific designs discussed.  The first designs introduced will be completely randomized designs, the most straightforward design when a researcher wants to test for differences amongst multiple treatments.  Optimal blocking strategies will then be presented as a variance-reducing technique, e.g. perhaps the researcher feels a subject's gender may significantly affect observations.  For each design we will discuss implementation, appropriate analysis and provide examples in SAS.  If time permits we may also introduce more complicated designs tailored specifically to the researchers attending the course.<br><br>Course files available here: <a href="http://www.lisa.stat.vt.edu/?q=node/2804" rel="nofollow" target="_blank">www.lisa.stat.vt.edu/?q=node/2804</a>.

Introduction to Design and Analysis of Experiments by Jonathan Stallings