Every scientist has to be a statistician these days, but not every scientist wants to be.
Reviews
04 January 2011
There are a lot of reasons to enthuse about the new release of Mathematica; across the board and not least (from my point of view) the statistics and probability coverage.
04 January 2011
With the latest incremental version update (8.1 to 8.5, now at service release 1), OriginLab’s increasingly versatile data graphics package sees useful improvements and new developments in a number of areas.
31 August 2010
Felix Grant reviews the bibliographic reference handler that doubles up as an information manager.
28 June 2010
Felix Grant reviews the latest iteration of Minitab's flagship statistics package.
16 June 2010
Felix Grant reviews the latest upgrades to Maplesoft's flagship computer algebra package and its high profile simulation sibling.
15 February 2010
Felix Grant finds that the latest version of Systat's statistical software shows evolution of capability and usability.
17 December 2009
Felix Grant tests the latest iteration of VSNi's statistical package, GenStat 12.
02 November 2009
Felix Grant reviews Grapher 8, the latest update to the page-oriented technical graphics software produced by Golden Software.
Pages
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Building a Smart Laboratory 2018 highlights the importance of adopting smart laboratory technology, as well as pointing out the challenges and pitfalls of the process
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Informatics experts share their experiences on the implementing new technologies and manging change in the modern laboratory
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This chapter will consider the different classes of instruments and computerised instrument systems to be found in laboratories and the role they play in computerised experiments and sample processing – and the steady progress towards all-electronic laboratories.
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This chapter considers how the smart laboratory contributes to the requirements of a knowledge eco-system, and the practical consequences of joined-up science. Knowledge management describes the processes that bring people and information together to address the acquisition, processing, storage, use, and re-use of knowledge to develop understanding and to create value
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This chapter takes the theme of knowledge management beyond document handling into the analysis and mining of data. Technology by itself is not enough – laboratory staff need to understand the output from the data analysis tools – and so data analytics must be considered holistically, starting with the design of the experiment