For researchers aiming to set up their experiments to enable a clean and easy analysis, diligent planning is vital for success. Careful experimental design facilitates maximal information gain from results and minimizes cost. In this short course, we will discuss the three basic principles of design of experiments, namely: 1) randomization (to ensure results are not biased by time, order, fatigue, etc.), 2) replication (to improve our estimation of the effects), and 3) local control of error (to reduce known variability). We will also use example data sets to illustrate the three principles, demonstrating how to enter and, if time permits, how to analyze the data in JMP. Specifically, we will work with one data set examining the effect of nozzle design on water jet performance (Theobald 1981), and another looking at how type of treatment affects gene expression in human leukemia cells (Cheok, et al. 2003). Any and all who have little to no background in basic statistical techniques and are interested in acquiring a short introduction to experimental design are invited to attend this lecture session.
Cheok, M. H., Yang, W., Pui, C. H., Downing, J. R., Cheng, C., Naeve, C. W., . . . Evans, W. E. (2003). Treatment-specific changes in gene expression discriminate in vivo drug response in human leukemia cells. Nature Genetics, 34(1).
Theobald, C. (1981). The effect of Nozzle design on the stability and performance of turbulent water jets. Fire Safety Journal, 4(1).
LISA Short Course: Design of Experiments from LISA on Vimeo.