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Rigorous Experimental Design in the Era of CRISPR, Big Data and COVID-19


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Andrew Chen

Event details


Register for this webinar here: https://neuronline.sfn.org/training/rigorous-experimental-design-in-the-era-of-crispr-big-data-and-covid19

Scientific rigor requires effective experimental or study design, logical reasoning, and sound strategies for analysis of errors for critical testing of specific models, in addition to adequate statistical methodology. Yet, didactic training in these essential research skills, beyond statistics, is given little emphasis in the education of science practitioners. Deficient logic frequently impairs actual experiments, grant proposals, and published studies.  Development of effective research designs is particularly challenging for junior researchers writing grants.  Inadequate understanding of the logic of the scientific process is widespread, and even impacts public health decisions, as evidenced by major errors and confusion in addressing the COVID-19 pandemic. This webinar addresses those challenges and introduces educational approaches to strengthening our comprehension of the principles of scientific inquiry necessary for the critical testing of explanatory models.

Panelists will present a general rubric for the critical evaluation of experimental design and will share exercises for teaching the necessary logic and error analysis in research practice. Examples will illustrate the process, as well as the benefits, of going from omic studies to rigorous hypothesis testing. 

Resources, including exercises and a basic rubric for tests of explanatory models, will be available through a new website.

Participants of this webinar will learn how to:

  • Critically assess tests of explanatory models that emerge from discovery-based studies 
  • Diagnose logical flaws in experimental and study designs
  • Diagram the logic of published studies

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