Question

Overall do you envision that this Statistics course will be beneficial for your career as a Health Professional?

Your discussion should include those topics you felt were:

(a) necessary

(b) not necessary

(c) interesting

(d) difficult

Your discussion should also include if you would have preferred to take this Statistics course as an in-class course instead of as an online class.

Answer 1

This is a very subjective question and there is never a one size fits all answer to this discussion. If we ask whether statistics is necessary as a subject, the answer is it depends on the context we are talking about.

For healthcare professionals it becomes necessary to understand basic statistical concepts and to be able to appraise scientific papers to see whether they answer the research problem in question, and to assess the robustness of results presented. Statistics is interesting to see how results compare and looking at the strength of the relationship (if any) that exists between the two outcomes. Also they play a significant role in systematic reviews and meta-analyses of subjects.

At its simplest level, statistics is about summarising (descriptive statistics) and presenting data (inferential statistics) in ways that accurately reflect and convey their meaning. The next level is hypothesis-testing – the process of systematically answering a research question of importance. Or validating a status quo with an alternative.

Basic examples of issues important to healthcare professionals and medical students include trying to ascertain whether a newly launched treatment or a drug treated to patient is better than an existing drug or whether a possible risk factor.

For example, low birth weight, is associated with a particular outcome, such as the likelihood of developing asthma. The essence of this is to begin by assuming that the treatment or risk factor has no effect; this is sometimes referred to as the null hypothesis. The likelihood that any difference between groups has arisen by chance is then calculated.

The level of difficulty depends on the explainability of the system. Statistical jargon can sometimes be confusing. Most books and research on statistics are written for the specialist with masters in statistics, often being full of formulae and jargon. This is unfortunate because computer programs for performing statistical tests are readily available, removing the need to perform long, complicated calculations. The most important part is the interpretability of the models and use it for relevant test cases. Concepts that often perplex non-researchers should be presented in a plain, straightforward way.

As a personal choice I would choose statistics as a subject as it gives an analytical approach to problem solving thus keeping irrationality out in our analyses.