If you’ve ever skipped over`the results section of a medical paper because terms like “confidence interval” or “p-value” go over your head, then you’re in the right place. You may be a clinical practitioner reading research articles to keep up-to-date with developments in your field or a medical student wondering how to approach your own research. Greater confidence in understanding statistical analysis and the results can benefit both working professionals and those undertaking research themselves.
If you are simply interested in properly understanding the published literature or if you are embarking on conducting your own research, this course is your first step. It offers an easy entry into interpreting common statistical concepts without getting into nitty-gritty mathematical formulae. To be able to interpret and understand these concepts is the best way to start your journey into the world of clinical literature. That’s where this course comes in - so let’s get started!
The course is free to enroll and take. You will be offered the option of purchasing a certificate of completion which you become eligible for, if you successfully complete the course requirements. This can be an excellent way of staying motivated! Financial Aid is also available.
Getting things started by defining study types Welcome to the first week of this course. We’ll be tackling five broad topics to provide you with an intuitive understanding of clinical research results. This isn’t a comprehensive statistics course, but it offers a practical orientation to the field of medical research and commonly used statistical analysis. The first topics will look at research methods and the collection of data - with a specific focus on study types. By the end of the lectures you should be able to identify which study types are being used and why the researchers selected them when you are reading a paper.
Describing your data With the next topics, we finally get started with the statistics. Have you ever looked at the methods and results section of any healthcare research publication and noted the variety of statistical tests used? You would have come across terms like t-test, Mann-Whitney-U test, Wilcoxon test, Fisher’s exact test and the ubiquitous chi-squared test. Why so many tests you might wonder? It’s all about types of data. In this week, I am going to tackle the differences in data which determine what type of statistical test we can use in making sense of our data.
Building an intuitive understanding of statistical analysis There is hardly any healthcare professional who is unfamiliar with the p-value. It is usually understood to have a watershed value of 0.05. If a research question is evaluated through the collection of data points and statistical analysis reveals a value less that 0.05, we accept this a proof that some significant difference was found, at least statistically.In reality things are a bit more complicated than that. The literature is currently full of questions about the ubiquitous p-vale and why it is not the panacea many of us have used it as. During this week you will develop an intuitive understanding of concept of a p-value. From there, I'll move on to the heart of probability theory, the Central Limit Theorem and data distribution.
The important first steps: Hypothesis testing and confidence levels In general, a researcher has a question in mind that he or she needs an answer to. Everyone might have an opinion on the question (or answer), but an investigator looks for the answer by designing an experiment and investigating the outcome. In the first lesson we will look at hypotheses and how they relate to ethical and unbiased research and reporting.We'll also tackle Confidence intervals which I believe are one of the least understood and often misrepresented values in healthcare research. The most common tests used in the literature to compare numerical data point values are t-tests, analysis of variance, and linear regression. In the last lesson we take a closer look at these tests, but perhaps more importantly, their strict assumptions.
Which test should you use? The most common statistical test that you might come across in the literature is the t-test. There are, in actual fact, a few t-tests, but the one most are familiar with, is of course, Student’s t-test and its ubiquitous p-value. Not everyone, though, knows that the name Student was actually a pseudonym, used by William Gosset (1876 - 1937). Parametric tests have very strict assumptions that must be met before their use is justified. In this lesson we take a closer look at these tests, but perhaps more importantly, their strict assumptions. Once you know these, you will be able to identify when these tests are used inappropriately.
Categorical data and analyzing accuracy of results Congratulations! You've reached the final week of the course Understanding Clinical Research. In this lesson we will take a look at how good tests are at picking up the presence or absence of disease, helping us choose appropriate tests, and how to interpret positive and negative results. We’ll decipher sensitivity, specificity, positive and negative predictive values. You'll end of this course with a final exam, to test the knowledge and application you've learned in this course. I hope you've enjoyed this course and it helps your understanding of clinical research.
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.
I have attempted taking courses or reading books on medical statistics earlier, and every time, I took a few baby steps and then aborted. I was good at maths in school, but hey, twenty years in the medical profession, and the confidence sags. This time, I got a bird's eye view of the entire subject, with sufficient detail where required. This course is comprehensive, without being intimidating, and focuses on an intuitive grasp of the subject. I can say for sure that I am more motivated now than ever before, in conducting clinical research the right way. The foundation stones have been laid. I can now build on this knowledge, without fear of statistics getting in the way.
What a great course! I highly recommend it to anyone who is interested in clinical research and wants to understand how statistics is used in clinical research. I loved all aspects of the course. The lecture videos were short and crisp. Dr. Klopper is very engaging and explained even the hardest concepts really well. The quizzes let you apply what you learn. The peer review assignments are a great way of soliciting and giving feedback. Learning this course has really enriched my statistics knowledge.
It was an excellent course; comprehensive and very well-explained, indeed without needing to apply much mathematics. Therefore, the course is perfect for most researchers, doctors or allied personnel wanting to learn or enhance their understanding on the statistics behind research, beginners or semi-advanced. I would only recommend the teacher to include an extra week on survival analysis, a very important and frequently misunderstood topic. Thank you for the nice course.
The material is very dense, but the explanations were good. I had to review the material a lot, but I think that is the nature of this topic. I loved the way the course was organized between videos, reading, tests and assignments. I especially benefitted from the real-world examples that were used in the material. In fact, I think the course could have included even more! I got out of it exactly what I wanted: a basic understanding and ability to assess a study's strengths and weaknesses. Very good use of my time!
Dr Klopper is an excellent teacher. The lectures were very well done and the lecture notes were helpful. Statistics is a difficult subject, but the concepts were explained clearly without too much complicated math. It's a very good course for learning how to read biomedical literature with a critical eye, in order to judge whether study results have been interpreted correctly by the authors or the authors have drawn conclusions that are not justified by the data.
Juan did a fantastic job in explaining basic statistic principles and using examples from medical journals to put theory into practice. After taking this course, the statistical section of the medical papers will not look daunting anymore. Highly recommend this course to health professionals who want to gain basic but crucial statistical knowledge!
I would like to thank Juan and the organisers of this course. I would recommend this course to everyone who needs to know about stats. This is the first course on stat that I have completed and understood in great depth. This course helps you to develop deep and thorough understanding of choices of stats tests and justification for the choice. I can't thank Juan enough. You've made difficulties in understanding stats in articles decrease to a great extent. I like that fact that you pull all the learnings together with a case study on how to link it all together. Thank thank you so much. I already recommended to a colleague. I will spread the news.
I am a physician-scientist, but never had a strong understanding of statistics. This course was excellent. It covered essentially all of the commonly used tests in medical and social research. Still, it was not overwhelming. It was clear and concise, yet had sufficient examples. I would say that the instructor, from South Africa, uses some phrases that might take a moment to fully grasp. I guess you could say the "lingo" is not 100% American. That is fine- after all this course is being studied by people around the world. I only mention this to suggest you listen to him carefully. Overall, an excellent course and an excellent experience!
This was a really good review for me of statistical concepts- having taken my last college level stats class 30 years ago! The topics selected were very relevant to understanding clinical research and Dr. Juan's lectures were clear, well organized and the right length to ensure understanding while maintaining student focus. I also like the fact that each week's quizzes incorporated previous weeks' concepts, which was a good review. Finally, the course also included a couple of case studies using real world research - I found this aspect to be a great review as well as more interesting than just going over stale notes.
Farooq Ahmedcompleted this course, spending 2 hours a week on it and found the course difficulty to be medium.
conducting and evaluating research is an integral part of medical education. medical professionals including doctors, nurses and paramedics who are pursuing their carriers as practicing doctors and nurses need to understand and practice research at every step of their carriers. i think this course is a must for all medical students both undergraduate and postgraduate and will enhance their understanding about research and skills of conducting and evaluating research. i as working as director of medical education in a medical college and will try to introduce these concepts in undergraduate medical curriculum
I would like to thank the team for this course. At first I had doubts but it actually provided me with a high understanding of general concepts as well as subtle details. Now I know where to click in some softwares and I'm even able, against all odds (ha, ha) to calculate a few things in Excel myself. I can talk and not look too stupid and even advise people about their research designs. Of course, there's still, for me, a huge area of improvement but I'm very thankful for these useful courses and proud to have passed this certification ! Will take it again though, to strengthen my understanding ;)
Dr George Harveycompleted this course, spending 2 hours a week on it and found the course difficulty to be medium.
I really enjoyed this course, more than anything it told me what are the important things to know and so guided my self-learning. The interactive sections were great and I'd like to see more of them, particularly for people who want to learn HOW to do the various tests. The Khan Academy videos on statistics and probability served as great adjuncts for exploring some of the statistical methods and concepts in more detail for those who are interested.
There were a fair number of typos in the written content.
This is a comprehensive course and serves as a refresher course for my ST101 more than 20 years ago. I like the first few chapters as the lessons went slowly with ample applications. It would be excellent if the last few chapters follow suit.
Overall, this is a very good course based on the content, speed, and flexibility. I really enjoyed re-learning them all through here - taking them slow and easy. I will be using some of the applications and topics learned here for my work. Thank you.
conducting and evaluating research is an integral part of medical education. medical professionals including doctors, nurses and paramedics who are pursuing their carriers as practicing doctors and nurses need to understand and practice research at every step of their carriers. i think this course is a must for all medical students both undergraduate and postgraduate and will enhance their understanding about research and skills of conducting and evaluating research.
Dr Juan Klopper is a great teacher and I thoroughly enjoyed the course. It was just at the right level for a researcher like myself, who has some idea about research, but finds the statistics difficult to understand at times.
I would like to suggest some sort of a platform, either with Dr Klopper or among the people who took the course, where we could discuss future research and relevant statistical methods, so that we could put into practice what we have learnt.
Great course!! If you are interested to involve yourself in clinical research, this is gonna be your foundation in statistical analysis. The teaching is easy to understand and it teaches about the principle underlying each test so we could easily understand each test. Besides, couples of real articles are used as case study and we can clearly identify the type of study, data type, statistical analysis with the aids from our tutor. Highly recommended !!
This course is really helpful in explaining the different types of commonly-used statistical analyses in clinical studies. I found that the lecturer gave clear lectures with relevant examples, especially that I haven't received any prior basics in statistics. However, I find that the different tests that are explained in both week 4 and 5 feels a little bit rushed, as I would have liked to have more explanations behind all the different tests.