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University of Cape Town

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


4.8 rating, based on 770 Class Central reviews

4.8 rating at Coursera based on 3229 ratings

Start your review of Understanding Clinical Research: Behind the Statistics

  • Overall good, but the course lacks practical examples like demos. E.g how to create dummy data for t-distribution using spread sheet software. Require more examples on nonparametric tests. I feel nonparametric tests are not explained properly. For example, rank sum doesn't make complete sense The course does not explain shortcomings of p value in larger samples. Lastly, there is no explanation on logistic regression that would have made this course complete. This course is nice overview for someone who wants to have basic understanding of clinical research.
  • good way to start with clinical statistic life. The course could help your life easier and change your attitude about research.
  • Anonymous
    Absolutely fascinating. Lacked this concepts, despite having graduated from Medical School recently. It is completely necessary to get in touch with all this, research in the medical field is fundamental. Dr Klopper´s explanations are crystal clear.
  • Anonymous
    Coursera's "Understanding Clinical Research: Behind the Statistics" is a highly informative and engaging course. The course is designed to give students a thorough understanding of the fundamental principles of clinical research, such as study desig…
  • 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.
  • Profile image for Iman Esmaili
    Iman Esmaili
    Outstanding: Understanding Clinical Research Online Course with an Exceptional Instructor!

    I recently completed the "Understanding Clinical Research" online course and it was an exceptional experience. The course content was comprehensive, covering everything from study design to ethics. The instructor was passionate, knowledgeable, and made complex topics easy to understand. The interactive nature of the course and the supportive learning community added immense value. I highly recommend this course for anyone interested in clinical research.
    However, what truly made this course outstanding was the instructor. His ability to explain complex concepts in an engaging manner made learning enjoyable and accessible.
  • Stefka Behova
    I really enjoyed this course. It is very well organised with clear objectives and a level of simplicity allowing a beginner to understand and acquire a very grasp on the subject. The information is presented in short easy to digest sections with reg…
  • Anonymous
    It was a great chance when I heard first about this course, as a medical student it helped me a lot to know more and build a solid knowledge about clinical research behind the statistics.

    From the types of research designs, through the sampling methods reaching the probabilities and statistical tests (each one for a specific study type) and measuring the performance of the tests in the study with predictive values .... nice experience I have earned throughout this course.

    It is highly recommended especially for the students who want to start doing research to get it as a 1st step to start.

    Especial thanks to Dr. Juan H Klopper for his efforts.
  • Anonymous
    "Understanding Clinical Research: Behind the Statistics" is a highly informative and engaging course offered by Coursera. The course is designed to provide learners with a comprehensive understanding of the basic principles of clinical research, inc…
  • Anonymous
    This was a fantastic and insightful course. The instructor delivered the lectures with some great practical examples. The course notes were very helpful and quizzes really tested the knowledge we had gained during the course. Although, I have worked with statistics before this course was a good choice for me as I gained more clarity and confidence on the concepts. I will recommend taking this course, it is worth the time and effort. Thank you Coursera, University of Cape Town and to the instructor for the time and efforts.
  • Profile image for Arnab Dasgupta
    Arnab Dasgupta

    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.
  • Anonymous
    It is just the perfect course for beginners or those who run away from reviews of articles and papers in the Journal. The course instructor takes time to explain each concept and the reason behind the choice of a particular statistical tool for data analysis. He demystifies the concept of types and classes of data.
    The addition of a summary page at the end of every season is particularly unique in this course, which helps to further understand the course.
  • Anonymous
    The course "Understanding Clinical Research: Behind the Statistics" is beneficial, logical and clear. It helped me get a better intuitive understanding of clinical research. It helped that it started from the very beginning. To fully understand the lessons, I also looked at other Youtube videos. Overall I enjoyed it and I feel that it has helped me a lot. Would recommend.
  • Anonymous
    This course is an ideal course for anyone interested in clinical research. It broadens ones knowledge on various important information in making and identifying research papers. I would definitely recommend this course to someone who is new to the research world and also people who have interest in learning more on how research works.
  • Profile image for G. Montserrath Gomez Santos
    G. Montserrath Gomez Santos
    Es un buen curso, te introduce al mundo de la estadística de manera general. Te lleva de mano desde termino muy sencillos de que es una muestra, tipos de estudios observacionales y experimentales. Además de que facilita la comprensión de los temas por que en cada lección se muestran ejemplos con diversos estudios reales.
  • Anonymous
    The course is interesting and gives a good foundational knowledge into understanding the statistics of medical/bio literature. The instructor is well-paced and very knowledgeable about the subject field. However I feel more hands-on project on the data on spreadsheets or other computer software could be integrated. Thank you.
  • A very organised course that has a smooth progressive approach in teaching the fundamentals of clinical research.
    The short video lectures by Dr Juan were so informative with a simple understandable language.
    I surely enjoyed it and honestly recommend it for those starting their career in clinical research.
  • Anonymous
    This course has been amongst the best courses I have attempted. I learnt a lot. It covered most important basic concepts and the teaching methodology also was very impressive and understandable. Diagrams and graphs were very helpful. and questions in quizzes were designed in a very thoughtful manner.
  • Anonymous
    This course has opened my mind to the different types of research designs and the various statistical tools used in analyzing research. I have learned a lot in a short time and I am certainly now more confident approaching different research articles—sincere thanks to Juan and the team.
  • Anonymous
    Reading medical literature makes much more sense to me now. I can actually finish reading the article and sift through data with intelligent thinking, I found answers to those biostatistic questions which I felt very silly asking and never asked. A big thx to Coursera team

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