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.
Understanding Clinical Research: Behind the Statistics
Overview
Syllabus
- 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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Reviews
4.9 rating, based on 834 Class Central reviews
4.8 rating at Coursera based on 3483 ratings
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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.
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Amazing course.If you are a beginner and someone who is interested in research then you must take this course to have the better understanding of the research paper.Don't be scared by the word "statistics" mentioned in the title as it doesn't involve complicated mathematics.They have tried to keep is as simple as possible.
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As someone deeply interested in the intersection of healthcare and statistics, I enrolled in the "Understanding Clinical Research Behind Statistics" course with high expectations. I can confidently say that it not only met but exceeded those expecta…
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good way to start with clinical statistic life. The course could help your life easier and change your attitude about research.
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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.
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The course gave me the confidence to face the career in Clinical Research. It is put together in a way that helps every beginner find a streamlined and systematic flow into the subject and field. The materials are easy to understand and follow.…
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This course is well-structured and highly informative, with the lecturer delivering content clearly and effectively. The explanations are straightforward, making complex topics like study design and statistical tests easy to understand. The lecturer uses practical examples and real-life scenarios to illustrate key concepts, which helps in grasping how to apply these methods in actual research. The course is particularly strong in breaking down different types of statistical tests and their uses, ensuring that students can confidently choose the right test for their data. Overall, the course is engaging and accessible, providing valuable insights into research methods and data analysis with a teaching approach that simplifies learning.
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This is is a great course especially for professionals within the health sector who as beginners want to grasp a basic understanding of clinical research in terms of understanding data and how best to collect, analyze and interpret in basic, clear and concise presentations. You will acquire knowledge on the basic data types, sampling methods, study types and their application, measures of central tendencies and dispersion of data, various tools/statistical test to analyze data and the indications for choosing one over the other with the assumptions that have to be met amongst several other factors. I am confident that just as this course has build my research skills and capacity, it will do same for all who take it as well.
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Very informative and enjoyable course. I took it to gain a more intuitive understanding of the statistics commonly used in medical research. The videos were relatively short, which made them easier to complete , and the key notes explained, concisely, the topic at hand. I love how the questions truly tested your understanding.
I'd suggest that, for questions that were answered wrong, more elaboration on why the correct answer was the correct one, as alot of the times, I'd still be confused about which answer was right and why.
Thank you so much for providing this course for free. Love from Yemen
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Arnab DasguptaI 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. -
This is a very useful course.
Organised in small lessons, with clear language and simple examples, lets one lear and understand the basics of the statistics present in most clinical papers.
We learn in samll steps, but in a steady way, allowing students to critically appraise the science we ar confronted with.
We learn at our own pace, get assured of our progress with simple tests.
The peer review testing is also a good idea, that makes us interact with other students.
Well done and very high value -
It was a very well structured course about explaining the general concepts of statistic methods and the first approach to research concepts. In my case it dissipated some doubts I had about certain related topics and the lecturer provides brief but well-explained definitions so it was a good start digging into this field of research with the course. I highly recommend it if you want to know more about the foundations of statistical methods used in research.
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Before I started this course, I really didn't understand most statistical analytical terms and how to use them. But, after completing it, I can confidently say I understand statistical concepts and it's applications. The use of relevant examples and quizzes was really helpful in understanding the concepts. I fully recommend this course to anyone seeking to understand the fundamentals of statistics in the clinical setting.
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Understanding Clinical Research: Behind the Statistics* is an excellent course that demystifies the statistical concepts used in clinical research. It breaks down complex topics into simple, relatable explanations, making it accessible for those without a strong math background. Ideal for healthcare professionals and anyone interested in grasping the basics of clinical research statistics.
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This course is great for getting a refresher on all different types of statistics and when to use them. Juan is an amazing teacher and very easy to follow. The workload is well-balanced, and the examples used are relevant (using clinical research papers). Overall good course for wanting to learn more about statistics applied to clinical research.
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I'm a total beginner in the field of medical statistics but this course have been just right.
I could understand almost all concepts because the course builds from the bases and iterates the concepts mentioned early in future lectures as well.
Thanks Dr Juan Klopper and all the team for this very fun and very valuable course! -
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…
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Thank you! I really liked this course, I had a basic knowledge of statistics, and here I refreshed some concepts, I learned a lot of tricks about statistical calculation and I am eager to apply these new skills in my own research works. Thank you for helping us advance our goals!!!
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The past six weeks I have learned, unlearnt and relearnt the research behind statistics and I must tell you it's been a wonderful experience. I am happy I was able to complete the course. Now I am more knowledgable about research.
Thank you Coursera for giving me the opportunity. -
A very good course covering the most important topics for starting any journey in clinical research. It’s well-organized and engaging, making complex concepts easy to grasp. Many thanks to the instructors and everyone involved for creating such a valuable learning experience!
