Media links for Biostats Course VHM 801 at AVC - Winter Semester 2026

This page provides links to media files and webpages used in the course. A vast selection of video clips on statistical topics is available at YouTube.

Scott Stephens supporting website (www.StevensStats.com)

• Video lectures for each chapter, including Your Turn problems
• Technology demonstrations (incl. Minitab)

Statistics links (specific topics)

• Example of serious misuse of probability/statistics: Sudden infant death syndrome (SIDS):
  • Article on Sally Clark case, including the open letter from The Royal Statistical Society on SIDS convictions
  • TED talk by Peter Donnelly on statistics and probability calculations, with particular focus on its use as juridical evidence

• Statistical inference:
  • Recommended: review paper on misinterpretations: Greenland et al. (2016), European Journal of Epidemiology 31, 337-350.
  • Press release from the ASA (American Statistical Association) on statistical significance and P-values
  • The ASA's statement on p-values: context, process, and purpose, The American Statistician 70, 129-133.
  • Moving to a World Beyond "p<0.05" (2019), (The American Statistician 73:sup1, 1-19).
  • The ASA's p-value Statement, One Year on (2017), (Significance 14, 38-41).
  • Sample articles in Nature: Baker (2016), Nature 531; Leek & Peng (2015), Nature 520 (in particular, the figure).
  • New England Journal of Medicine: Editorial (New Guidelines for Statistical Reporting) (NEJM, 2019:381, 285-286); Instructions for authors (in particular, Statistical Reporting Guidelines).
  • Big little lies: a compendium and simulation of p-hacking strategies, Royal Society Open Science 10, 220346.
  • "Absence of evidence is not evidence of absence" (British Medical Journal, 2004:328, 476-477).

• Sample size and power calculations:
  • Video: How not to collaborate with a biostatistician (author: josiesjavamama, previously at www.extranormal.com)
  • "The tyranny of power: is there a better way to calculate sample size?" (British Medical Journal, 2009:339, 1133-1135).

• Flowcharts for statistical analysis (many of these exist):
  • Comprehensive chart for SAS, Stata, SPSS, and R (Institute for Digital Research and Software, UCLA)
  • Simple, for quantitative outcomes only (author: Paul Marr)
  • table from PSLS 3/4e (Moodle access),
  • simple table used in course (with method names),
  • simple diagram for post-ANOVA analysis,

• Journal articles:
  • "Kurtosis as Peakedness, 1905-2014. R.I.P." (The American Statistician, 2014:68, 191-195; full access at UPEI and Moodle).
  • "The birthday problem" (Significance, 2007:4, 124-127)
  • "Simple tools for understanding risks: from innumeracy to insight" (British Medical Journal, 2003:327, 741-744).
  • "The probable error of a mean" (Biometrika, 1908:6, 1-25); for context about this paper, see also this article.
  • "Applications of "Student's" distribution" (Metron, 1925:5, 90-104).
  • "Adaptive aerial righting during the escape dropping of wingless pea aphids" (Current Biology, 2013:23, R202-R203).
  • "Comparative study of doramectin and fipronil in the treatment of equine chorioptic mange" (Veterinary Record, 2007:161, 335-338; UPEI Access).
  • "Misuse of multiple comparison tests and underuse of contrast procedures in aquaculture publications", (Aquaculture 437, 344-350).

Images

• Normal wordgrams constructed by Fikret Er, Anadolu University, Turkey (idea attributed to Youden (1962) and Graham (1990)): classical, modern,
• Matthew Freedman (2006), A visual comparison of normal and paranormal distributions, J Epidemiol Community Health 60: 6.

Statistics and probability humour

• It is 1941 and the Germans are bombing Moscow. Most people in Moscow flee to the underground bomb shelters at night, except for a famous Russian statistician who tells a friend that he is going to sleep in his own bed, saying that "There is only one of me, among five million other people in Moscow. What are the chances I'll get hit?"
  He survives the first night, but the next evening he shows up at the shelter. His friend asks why he has changed his mind. "Well," says the statistician, "there are five million people in this city, and one elephant in the Moscow Zoo. Last night, THEY GOT THE ELEPHANT!" (Internet source no longer accessible)

• A famous statistician would never travel by airplane, because he had studied air travel and estimated that the probability of there being a bomb on any given flight was one in a million, and he was not prepared to accept these odds.
  One day, a colleague met him at a conference far from home. "How did you get here, by train?"
  "No, I flew"
  "What about the possibility of a bomb?"
  "Well, I began thinking that if the odds of one bomb are 1:million, then the odds of two bombs are (1/1,000,000) x (1/1,000,000). This is a very, very small probability, which I can accept. So now I bring my own bomb along!" (Internet source no longer accessible)