Michael Wood: academic interests

michael.wood@port.ac.uk or michaelwoodslg@gmail.com

I am now retired but am keen to carry on working on a few of the themes covered by the links below. The main ones are the virtues of simplifying academic knowledge, especially statistics, and the peer review system.

       

Making sense of statistics: a non-mathematical approach (Book published by Palgrave, 2003)

    

Simple knowledge: why academic knowledge should be simplified

    

Brief notes on statistics: old version, new version

    

Brief notes on research methods (without the pointless jargon)

    

Other teaching notes, slides, etc

    

A few conference presentations

    

Sceptical Academic Blog

   

Times Higher Scholarly Web column (26 June, 2014) on my blog post about the closure of Cambridge University

   

Resample.xlsx: a spreadsheet for resampling, bootstrapping, etc

   

Other software

   

Videos on statistics

   

Ancestral memoirs: grandfather, great aunt

 

Selected articles

 

Simple Methods for Estimating Confidence Levels, or Tentative Probabilities, for Hypotheses Instead of P Values, Methological Innovations, 2019.

 

How sure are we? Two approaches to statistical inference. (2018). arXiv:1803.06214 [stat.OT] or click here.

 

Making statistical methods more useful: some suggestions from a case study. Sage Open, vol. 3, no. 1, 2013 or click here. Spanish version.

 

Journals, repositories, peer review, non-peer review, and the future of scholarly communication (2013), arXiv:1311.4566 [cs.DL] or click here.

 

Maths should not be hard: the case for making academic knowledge more palatable. Higher Education Review, 34(3), 3-19, 2002. Click here for a copy.

 

I’ll make it simple. Times Higher, 30 August 2002.

 

Simplifying Academic Knowledge: Opportunities, Benefits and Barriers (2015). https://ssrn.com/abstract=2687046 or click here.

 

The role of simulation approaches in statistics. Journal of Statistics Education, 13(3), http://www.amstat.org/publications/jse/v13n3/wood.html, 2005.

 

Bootstrapped confidence intervals as an approach to statistical inference. Organizational Research Methods, 8(4), 454‑470, 2005. click here

 

The reliability of peer reviews of papers on information systems. Journal of Information Science, 30(1), 2-11 (with Martyn Roberts and Barbara Howell, 2004). click here

 

The journal of everythingTimes Higher, 22 April, 2010.

 

Citation games: comments on the paper by Annette RisbergNotework: Newsletter of the Standing Conference on Organization and Symbolism, May 2005, 26-8.

 

The case for crunchy methods in practical mathematics. Philosophy of Mathematics Education Journal, 14, 2001. click here or here

 

The Pros and Cons of Using Pros and Cons for Multi-Criteria Evaluation and Decision Making (2009).  https://ssrn.com/abstract=1545189 or http://dx.doi.org/10.2139/ssrn.1545189

 

Are “qualitative” and “quantitative” useful terms for describing research? Methodological Innovations Online5(1) 56-71 (with Christine Welch, 2010). Copy in SSRN

 

Anecdote, fiction and statistics - the three poles of empirical methodology. Click here.

 

Prospecting research: knowing when to stop. Marketing Letters, 12(4), 299-313 (with Richard Christy, 2001). click here

 

Sampling for possibilities. Quality & Quantity, 33, 185-202 (with Richard Christy, 1999). click here

 

Researching possibilities in marketing. Qualitative Market Research, 2(3), 189-196 (with Richard Christy, 1999). click here

 

The notion of the customer in total quality management. Total Quality Management, 8(4), 181-194, 1997. click here

 

Computer packages as cognitive paradigms: implications for the education of accountants. Journal of Accounting Education, 15(1), 53-69 (with Philip Cahill and James Hicks, 1997). click here

 

Statistical inference using bootstrap confidence intervals. Significance, Volume 1 (4), 180-182, 2004. click here

 

Statistical methods for monitoring service processes (1994). International Journal of Service Industry Management, 5(4), 53-68. click here

 

values, confidence intervals or confidence levels for hypotheses? (2014).  arXiv:0912.3878v5 [stat.ME]

 

Bootstrapping confidence levels for hypotheses about regression models (2012).  arXiv:0912.3880v4 [stat.ME] 

 

Statistical process monitoring in the 21st century (2002). In J. Antony & D. Preece (eds), Understanding, managing and implementing quality: frameworks, techniques and cases (pp 103-119). London: Routledgeclick here

 

The use of resampling for estimating control chart limits. Journal of the Operational Research Society, 50, 651-659 (with Mike Kaye and Nick Capon, 1999). click here

 

User-friendly statistical concepts for process monitoring. Journal of the Operational Research Society, 49(9), 976-985 (with Nick Capon and Mike Kaye, 1998). click here