Molecular Oncology and Biostatistics

Material for the biostat module

  • Lecture notes
  • Lab 1 data
  • Lab 4 data
  • Reading
  • Links

Lecture notes and handouts

  • August 30: Introduction to study design
    Handout / Problem solutions / Presentation / Discussion lung cancer
  • September 14: Analysis of variance
    Handout / Presentation / Example: COX2 (with answers)
  • September 22: Analysis of variance and interactions
    Handout / Presentation
  • September 29: Clinical trials
    Handout / Problem solutions / Presentation / Discussion phases of clinical trials
  • Oct 3: Statistical power Handout
  • Oct 4: Diagnostic tests Handout
  • Oct 11: Introduction to epidemiology I
    Introduction to epidemiology / Data Quality / Measures of disease
    Causality / Case-control studies / Cohort studies
  • Oct 12: Introduction to epidemiology II
    Other study types / Randomized controlled trial
  • Oct 17: Introduction to survival analysis
    Handout / Presentation

Back to top

Lab 1 data (p53 activation assay)

Short introduction to R/Rcmdr (same as spring term)

Morning session
1 JH.txt 10 Luwam.txt 11. Jason.txt 2 K SS.txt
3 LA.txt 4 ZO.txt 5 AH.txt 6 EL.txt
7 AM.txt 8 AS.txt 9 HW.txt
Afternoon session
AM.txt Christina.txt HC.txt
JohnAdrian.txt JohnEmmee.txt LI.txt
NathalieSofie.txt NP.txt QiLe.txt

Back to top

Lab 4 data (cytotoxicity assay)

Morning session
Lab4_1 JH.txt Lab4_10 Luwam.txt Lab4_11. Jason.txt
Lab4_2 K SS.txt Lab4_3 LA.txt Lab4_4 ZO.txt
Lab4_5 AH.txt Lab4_6 EL.txt Lab4_7 AM.txt
Lab4_8 AS.txt Lab4_9 HW.txt
Afternoon session
Lab4_AM.txt Lab4_Christina.txt Lab4_HC.txt
Lab4_JohnAdrian.txt Lab4_JohnEmmee.txt Lab4_LI.txt
Lab4_NathalieSofie.txt Lab4_NP.txt Lab4_QiLe.txt

Back to top

Requirements & preparatory reading

The statistics part of the course assumes that you have (had, at least) some familiarity with basic statistical concepts:

  • Descriptive statistics (means, standard deviations, standard errors)
  • Hypothesis testing and p-values (specifically t-test)
  • Confidence intervals
  • Simple linear regression
If you have passed the exam for the course Biostatistics (1BI009) in T4 of the Biomedicine program, you should be good to go. But even if you have not, these subjects will be covered in almost any introductory statistics course or module.

In the same manner, if you want to do extra reading on the side to refresh your memory, almost any text will do, but you could do much worse than one of the following ones:

  • M. Bland: An introduction to medical statistics, 3rd ed. Oxford University Press, 2000.
  • D. Altman: Practical statistics for medical research, 2nd ed. Chapman & Hall, 1999.
There is also a couple of useful statistical texts avaiable from KI's collection of electronic texts, e.g. look for "Statistics at square one" at ebrary.

Back to top

Useful links

  • Ressources for R
  • Statistics notes of the BMJ
  • Sample size program Piface
  • CONSORT clinical trial checklist
  • NIH registry of clinical trials

Back to top

Content by Alexander Ploner, 2011-09-08. Designed by FlipDarius.