Understanding Clinical Research: Behind the Statistics

University of Cape Town via Coursera

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Provider

Coursera
Pricing

Free Online Course (Audit)
Languages

English
Certificate

Paid Certificate Available
Duration & workload

6 weeks long, 27 hours worth of material
Sessions
Subtitles

Arabic, French, Portuguese, Italian, German, Russian, English, Spanish

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Overview

Class Central Tips

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.

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

Charts

#1 in Subjects / Mathematics / Statistics & Probability
#2 in Subjects / Health & Medicine / Health Care
#1 in Subjects / Health Care / Clinical Research

Reviews

4.8 rating, based on 731 Class Central reviews

4.8 rating at Coursera based on 3040 ratings

Start your review of Understanding Clinical Research: Behind the Statistics

Pardha Sai Kumar @saikumar

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.
Anonymous

The statistics behind this course has taught alot what I missed about statistics in my undergraduate degree program, this is one of the best course I have ever attended. I have the course and I can now challenge any data analysis that comes my way.
Mustapha Mubarak Jolayemi

It was a great course and a very explanatory one, the tasks given assisted really well in applying what was thought, I also love the structure of the course.
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 regular...

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 regular tests to check memory and improve further. I undertook the course at a higher speed due to pressure from an upcoming event in my career. Yet, I was able to retain and comfortably use the information I learned. Now reviewing research articles is not scary. A good tip for participants - please use the peer reviewing stations as opportunities to improve. The more peers you review the better understanding you will gain on checking research papers. I definitely recommend this course to everyone who needs good basic knowledge on clinical research.
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...

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 course begin from scratch. 2. The course deals about the statistical concepts to know to understand the clinical research and 3. The course structure is excellent (statistics made easy!!!). It is a wonderful course if your intention is to understand, even criticise, the statistical methods in the medical literature. And a good beginning for your own basic research.
I really thank Dr Juan Klopper, and everybody else involved, for this excellent course. Really awesome. to the point that I am starting to love when I come to the methods/results section of papers!!!
Just reading abstract and conclusions of a paper is an extremely bad habit that most of us do on a regular basis. Most of the time because many of us do not understand the rationale behind the numbers. This course has been of great help to me. Undoubtedly, I would recommend it to anyone wishing to acquire the basic knowledge to read Methods/Results of any paper and understand its reliability.
My most sincere thanks to Dr Klopper and the whole team. And thanks Coursera for providing these wonderful opportunities. And free!!
Najmee Adulyarat @17jjy

good way to start with clinical statistic life. The course could help your life easier and change your attitude about research.
Bhavna Krishnan

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.
Anonymous

The course presentation is clear and as simple and sensible as it needs to be for beginners. The lecturer provides relatable and interesting examples to illustrate key points. Their enthusiasm for the topic and the wider context is also inspirational. The questions in the tests are well set out (engaging). The written summaries were helpful too. I look forward to watching and learning more from this lecturer on their YouTube videos. The lecturer seems to have excellent teaching skills and teaches from the heart. Thank you very much to Dr Juan Klopper and UCT.
Muhammad Hamad Haleem

This course is a beginner course for those who are interested in learning basic concepts of research. The course helps us develop an understanding about research and how to interpret different published articles. Dr. Klopper is an amazing academic and teacher who makes different complex concepts simple to understand and applying those concepts. Additionally, the tutorials were of great help. Overall, the following concepts will be discusssed: Types of research, Sampling techniques, Statistical test and interpretation of graphical representation of data.
Anonymous

This course helps in understanding the basic concepts of Clinical research without mathematical applications and various statistical analyzing methods, tests to gain knowledge about statistics. This 6-week course provides great exposure and knowledge in understanding statistical approach in clinical trials. The video sessions by Dr. Juan H Hopper were informative and the key notes gives us a clear view about the courses. Weekly assignments, graded quiz and examinations helps to test your knowledge in this course.
Its a worthy course
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.
Aedrian Abrilla @aaabrilla

A must-take course for anyone, regardless of background, interested in having a good grasp of the medical literature.
Anonymous

I found this course very interesting for my current role as a Data Manager. I have just taken over as Data Manager of a renowned research institution. I needed to learn real time and make impact on the job and this course is in right direction for me.

I will recommend this course to my peers and colleagues who are in similar positions which will be a great help to them. Thank for the designed of the problem.

My only concern was it was more of reading than a little statistical applications. I will recommend that you try to add some statistical practical sections where learners can create a demo for real life situation. It was a wonderful course. Thank a millions
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....

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. However, much emphasis was given to the formulas and tinkering with numbers instead of wisely knowing how to use the different statistical tools in the various scenarios. This course was magnificent in providing a bird's eye view of how to best approach statistical analysis of information. The framework was enlightening and gave me tools to better interpret medical literature as well as to how to study data from my own databases. I would have loved a more in-depth approach to non-parametric testing and to analysis of categorical data points. Nevertheless, the course has made a great contribution to my statistical acumen. Thanks Juan and the team and congratulations to you too for having put together this useful course.
Anonymous

A very informative course where the basics of statistics was explained in a simple and effective manner. I enjoyed the course and learned a lot form the lectures and practice tests. The course was well structured. Dr Klopper is well articulated and explained each topic with great care and precision. This is definitely something I advise all hopeful post graduate students to enrol in

Thanks again
Anonymous

Really good course. The course exposes the learner to a plethora of different methods from setting a hypothesis to analyzing data in research papers. It gives a deeper understanding about statistics as not just math but from a clinical research point of view.

I definitely think it is a course worth taking as it really makes statistics interesting & fun.
Anonymous

Thank you for this well presented course. Although it is not an in-depth statistics course (it does not claim to be), it is useful towards achieving a general understanding of statistical concepts. The video presentations are nicely paced and the assignments and quizzes force one to revisit previous topics, so that concepts do eventually 'stick'.
Anonymous

I learnt so much during this course. I had a better understanding on importance of data analysis in research, using the appropriate data tool to analyse your data in scientific research. I also gained skill to be able to better review scientific literature. Thank you to all the lecturers and organisers of the course. Thanks Coursera .
Anonymous

very good course to help start understanding core concepts of clinical research. Covers basic statistical analysis and interpretation and starts to touch on more advanced topics. Everything a young doctor or researcher needs to get goin in the world of clinical statistics.
Anonymous

It was a pleasant and highly educational course, it captures key statistical concepts which are a good base for further expanding on the topic. Dr. Klopper is explaining very clearly and in a intuitively manner, backing up his statements with effective examples.