A Crash Course to Biostatistics and What You Can Expect After

The Oxford Journal of Life Sciences, Mathematics and Physical Sciences defines Biostatistics as a field necessary to “advance statistical science and its application to human health and disease, with the ultimate goal of advancing the public’s health”. It is a branch of statistics focused on all the data related to living organisms, they analyse and interpret obtained data. 

Biostasticians mainly address health-related questions such as whether or not smoking increases Alzheimer Disease, the life-expectancy of a cancer patient, the potency of a vaccine against COVID-19. They collaboratively work with surgeons, geneticists and biochemists to ensure that enough data “backs up” any scientific observations or treatments. Biostasticians also identify any missing data or biases which have emerged in the conducted scientific or clinical studies. Essentially, they compile data to draw conclusions then presented in research proposals needed to receive grants. 

Scrunching and interpreting any and all data is particularly important when publishing association or correlation studies (for example links between genetic mutations and disease likelihood), cutting down on unnecessary medical procedures proven to be inefficient and explaining biological perturbances. Careful interpretation of clinical studies particularly when comparing the effects of a drug versus of a placebo rely on careful statistical analysis.

Two key statistical concepts include:

  • P-value: describes how likely you are to have found a particular set of observations if the null hypothesis were true. The lower the p-value the greater the statistical significance of the observed difference. In biology usually, when a p-value < 0.05 it is considered statistical significant.
  • Multiple testing: when multiple individual hypothesis tests are tested at once, the error rate of these individuals tests no longer represent the error rate of the combined set of tests. As such, potential error rates need to be corrected for example using Bonferroni correction or the risk of having false positives increases. 

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Most Biostatisticians practice with a master or doctoral degree and examples of possible Bachelor of Science degrees include Mathematics, Statistics, Psychology or Computer Science. They are highly sought after in the job market for their strong mathematical, logical thinking, critical analysis and communication skills. Biostatisticians need to keep updated with the most recent literature and equipped with basic programming skills (Python).  

With a Biostatistics degree you can expect to be employed in health organisations, universities, private or public agencies. If you wish to positively impact human health, limit the spread of diseases and identify death causes amongst different geographical populations, you should definitely consider such a path.