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Understanding Clinical Research: Behind the Statistics

University of Cape Town via Coursera


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. Here we’ll provide an intuitive understanding of clinical research results. So this isn’t a comprehensive statistics course - rather it offers a practical orientation to the field of medical research and commonly used statistical analysis. The first topics we will look at are research methods and data collection with a specific focus on study types. By the end, you should be able to identify which study types are being used and why the researchers selected them, when you are later reading a published paper.
  • Describing your data
    • 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. This week I am going to tackle the differences in data that 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 to answer. Everyone might have an opinion on this question (or answer), but a researcher looks for the answer by designing an experiment and investigating the outcome. First, 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.

Taught by

Dr Juan H Klopper

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4.8 rating, based on 623 reviews

Start your review of Understanding Clinical Research: Behind the Statistics

  • Bhavna Krishnan completed this course.

    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.
  • Arnab Dasgupta completed this course.

    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.
  • Bruce Thompson completed this course, spending 3 hours a week on it and found the course difficulty to be medium.

    There were a number of occasions during this course when "I got it!" This is a brilliant course for someone who reads a lot of research but skips Methods and just concentrates on the graphs in the Results sections. My last formal course in stats was 40 years ago and this was just right for me. Now I understand what I'm reading! Maybe I'll even do some research myself.

    I loved the Dr Klopper's short videos and well-laid-out keynotes. The tests and assignments were just hard enough to make me think, not too hard to make me give up. I enjoyed the peer-review as well.

    A painless reintroduction to statistics.
  • Anonymous

    Anonymous completed this course.

    As a surgeon I had some knowledge about statistics before undergoing the course. But really not very much. For a dummy, facing a statistics course might be challenging. But not this particular course. And basically for three important reasons: 1. The...
  • A must-take course for anyone, regardless of background, interested in having a good grasp of the medical literature.
  • Anonymous

    Anonymous completed this course.

    After having dealt with evidence-based reading I had hit repeatedly a hard wall when interpreting results from databases I have developed. I had been to one semester of epidemiology in university a few years ago and statistics was part of the curriculum....
  • Anonymous

    Anonymous completed this course.

    This was an exitting experience and even a very busy person and can take it. It useful because it introduces the understanding of a lot words common in articles, what makes a article reading more clear. Also gives bases in how to start a research intrducing...
  • Anonymous

    Anonymous completed this course.

    I found this course good for beginners. Although I have only high school education I didn't find it hard.
    I learned a lot of new terms and understood the basics of some interesting statistical concepts.

    The lessons were very clear, the use of graphs helped me a great deal, Teaching free data retrieval and analysis tools was cool, and the Keynotes were great for review.
    The quizzes and tasks are fair, and easier then i expected.

    D.R. Klopper Thanks a lot,
    You were very pleasant and you seem to have sincere interest in the subject and teaching it.
    I promise that if i publish a research, I won't forget to enable free accesses to the data!
  • Profile image for Darwin H. Firayner
    Darwin H. Firayner

    Darwin H. Firayner is taking this course right now, spending 5 hours a week on it and found the course difficulty to be easy.

    This course has been very helpful to me. I was lost trying to conduct a research in order to apply for my title of MD. Dr Koppler and his team have managed to turn a hard topics as are statistics and research into very easy, accessible and even fun subjects. This course has made see clinical research differently. I feel that I've got the basic knowledge to conduct more complex clinical researches with a better quality. Furthermore, English isn't my native language; nonetheless, I've understood almost all the videos and lectures. With nothing more to add, I deeply thank Dr Koppler and his team for this piece of valuable information and I urge people interested in learning about clinical research and statistics to enrol in this course.
  • Anonymous

    Anonymous completed this course.

    Overall: The material was clear and well presented. It also covered the essentials of clinical statistics. The content seems appropriate for beginners but also those with prior experience who need a refresher or a different perspective on the topic. Altogether, it was a useful course. On a personal note: I would have liked more "exercise" with the assignments and a lengthier focus on the topics covered in the last weeks of the course (where content now accumulates and integrates more knowledge and analysis types). A big challenge remains selecting and interpreting the right analyses for a particular biological question and examples and more exercises for this topic would have been helpful.
  • Anonymous

    Anonymous completed this course.

    This course is one of the most organized and systematic courses on basics of research I have ever attended, as they start from the scratch taking you to great comprehensive understanding of research papers. They start with you from the types of studies and types of data, and going in depth with understanding the P-value, confidence interval, odds ratio, types of statistical tests. etc.
    A good advantage in this course as well that it doesn't take you in the maze of mathematics of calculations that are confusing for most of us because they are focusing that you understand these items and values and not calculating them by yourself.
    I suggest this course for anyone dealing with researches as a start.
  • Anonymous

    Anonymous completed this course.

    I really recommend this course. I am a recently graduated medical student with an interest in clinical research, and this helps a lot in understanding published papers, as well as with my own future research. It's a must if you want to better understand the statistics in a very friendly way.

    The quizzes are very helpful to reinforce what was taught throughout the videos and key notes.
    You can decide if you finish each week in one or more days. It has a flexible schedule, which is very helpful when you don't have all the time in the world to sit in a class.

    When I began the course, I wasn't going to pay for the diploma, but I believe it is worth it, definitely including it on my CV.
  • Anonymous

    Anonymous completed this 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!
  • Profile image for Theerabhat Damrongsantipitak
    Theerabhat Damrongsantipitak

    Theerabhat Damrongsantipitak completed this course, spending 2 hours a week on it and found the course difficulty to be medium.

    If you didn't learn the statistic's calculation : don't be afraid.
    The Instructor is lecturing made it simple to understand although you didn't know math.
    The contents emphasize in understanding clinical's research : Type of research, Variable, Method and statistical analysis of research, Interpretation of research results.
    The peer review assessment make you more confident in reading and interpret the clinical research.
  • Anonymous

    Anonymous completed this course.

    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.
  • Anonymous

    Anonymous completed this course.

    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.
  • Anonymous

    Anonymous completed this course.

    A very useful course for those who need to figure out what the result of statistical analysis of study research says. The teacher is very accessible to submit material for training, for which I want to thank him. Also visited his page on YouTube, a lot of interesting material on statistics and programming in medicine. Such a versatile specialist is really a genius, thanks for the work !!!
  • Anonymous

    Anonymous completed this course.

    This course is very educative especially for people in the medical field. I have learned alot about clinical research and how to look at different papers that have been published.
    The information shared here is very important for anyone interested in doing any form of research. How to decide on the method and statistical analysis has been very well covered here.

  • Anonymous

    Anonymous completed this course.

    I enjoyed a lot this course! I recommend it if you are interested in understand how clinical research works and how statistics are used. I think its for everyone because it is short but very well explained, what makes it really easy to stay motivated. Finally, this course actually made me comprehend those topics that I was struggling with, so im very grateful.
  • Anonymous

    Anonymous completed this course.

    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!

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