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A01=Stanley E. Lazic
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Experimental Design for Laboratory Biologists

English

By (author): Stanley E. Lazic

Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (https://stanlazic.github.io/EDLB.html) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry. See more
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A01=Stanley E. LazicAge Group_UncategorizedAuthor_Stanley E. Lazicautomatic-updateCategory1=Non-FictionCategory=MBGLCategory=PBWHCategory=PDNCategory=PSCOP=United KingdomDelivery_Delivery within 10-20 working daysLanguage_EnglishPA=In stockPrice_€100 and abovePS=Activesoftlaunch
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Product Details
  • Weight: 1100g
  • Dimensions: 193 x 252mm
  • Publication Date: 08 Dec 2016
  • Publisher: Cambridge University Press
  • Publication City/Country: United Kingdom
  • Language: English
  • ISBN13: 9781107074293

About Stanley E. Lazic

Stanley E. Lazic holds a PhD in Neuroscience and a Masters degree in Computational Biology from the University of Cambridge and has conducted research at the University of Oxford the University of Cambridge and Harvard University Massachusetts. He has written several papers on reproducible research and the design and analysis of biological experiments and has published in Science and Nature. He is currently a Team Leader in Quantitative Biology (Statistics) at AstraZeneca.

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