Understanding Clinical Research: Behind the Statistics from Coursera

What's inside

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Examines medical research practices and results, including why researchers select specific study types to gather data

Provides an easy and practical entry into interpreting common statistical concepts without requiring a deep dive into mathematical formulas

Provides an intuitive understanding of the concept of a p-value and explores the Central Limit Theorem and data distribution

Covers a range of statistical tests, including t-tests, analysis of variance, and linear regression, and their strict assumptions

Addresses the accuracy of results and guides learners in choosing appropriate tests and interpreting positive and negative results

Reviews summary

Understanding clinical research: the stats

learners say this course is largely positive and engaging. It provides an intuitive understanding of research study types, data types, and the statistical tests used in clinical research without the need for complex mathematics. The course is particularly helpful for those who want to improve their ability to read and understand research articles. According to students, the strengths of the course include: * Provides a clear and concise explanation of basic statistics used in clinical research. * Uses real-world examples and case studies to illustrate concepts. * Includes interactive quizzes and assignments to reinforce learning. * Presented by an enthusiastic and knowledgeable instructor. * Well-structured and easy to follow, with short video lectures and supplementary notes. Some areas for improvement mentioned by learners include: * More explanation on certain concepts, such as degrees of freedom. * Opportunities to perform simple calculations and use informatics programs like R. * Deeper coverage of non-parametric tests. Overall, students found this course to be a valuable introduction to the statistics behind clinical research and would recommend it to others.

The course does not require you to perform complex mathematical calculations. This makes it accessible to learners with a variety of backgrounds.

"Provides an intuitive understanding of research study types, data types, and the statistical tests used in clinical research without the need for complex mathematics."

The course is well-structured and easy to follow, with short video lectures and supplementary notes. This makes it easy to learn at your own pace.

"Well-structured and easy to follow, with short video lectures and supplementary notes."

The course is presented by an enthusiastic and knowledgeable instructor. This makes the learning process more enjoyable and engaging.

"Presented by an enthusiastic and knowledgeable instructor."

The course includes interactive quizzes and assignments that help you to apply what you learn. This is a great way to reinforce your understanding of the material.

"Includes interactive quizzes and assignments to reinforce learning."

An intuitive understanding of the different types of research studies, data types, and statistical tests that are used in clinical research. This is a great foundation for further learning in statistics.

"Provides a clear and concise explanation of basic statistics used in clinical research."

"Uses real-world examples and case studies to illustrate concepts."

The course could provide a deeper coverage of non-parametric tests.

"Deeper coverage of non-parametric tests."

The course could include more opportunities for learners to practice performing statistical calculations.

"Opportunities to perform simple calculations and use informatics programs like R."

The course does not go into great depth on any one topic. This may be a drawback for learners who are looking for a more comprehensive understanding of statistics.

"More explanation on certain concepts, such as degrees of freedom."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Understanding Clinical Research: Behind the Statistics with these activities:

Review basic math skills

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Ensure you have a strong foundation in basic math skills to support your understanding of statistical analysis.

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Review topics such as algebra, probability, and calculus.
Take practice problems to test your understanding.

Review basic probability theory concepts

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Strengthen your foundation in probability theory, a key component in understanding medical research statistics.

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Review lecture notes or textbooks
Solve practice problems

Review statistics fundamentals

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Brush up on basic statistical concepts to strengthen your understanding of the course material.

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Go over your notes or textbooks from previous statistics courses.
Complete online practice problems or quizzes.

12 other activities

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Watch a video tutorial on interpreting p-values and effect sizes

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Enhance your understanding of the importance and nuances of p-values and effect sizes in medical research.

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Find a reputable video tutorial (e.g., YouTube, Khan Academy)
Watch and understand the concepts

Do sample problems in Statistics

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Practice interpreting statistical analysis and results by doing sample problems.

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Find a set of sample problems online or in a textbook.
Work through the problems, taking your time to understand the concepts.
Check your answers against the provided solutions.

Join a study group with classmates

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Collaborate with peers to review course material, work through problems, and quiz each other.

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Find or create a study group
Meet regularly to discuss course content
Work on practice problems together

Form a study group

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Collaborate with peers to review and discuss key concepts.

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Identify classmates who share your interest in forming a study group.
Meet regularly to discuss class materials and work through practice problems.

Explore online resources for statistical analysis

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Expand your knowledge by engaging with online tutorials and resources.

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Search for reputable websites or platforms offering tutorials on statistical analysis.
Select a specific topic or concept to focus on.
Follow the tutorials, complete exercises, and apply what you learn.

Follow a guided tutorial on confidence intervals

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Gain a clear understanding of confidence intervals and their interpretation in medical research.

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Find a reputable online tutorial (e.g., Coursera, edX)
Watch the tutorial videos and complete the exercises

Practice t-test problem sets

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Solve a variety of t-tests to develop a more intuitive understanding.

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Find a reputable source for t-test practice problems.
Set aside 1 hour to work through the problems.
Review your answers with a classmate or tutor for feedback.

Create a course summary document

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Improve your retention and understanding by compiling key concepts, notes, and insights from the course.

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Go through your notes, assignments, and quizzes
Summarize key points and concepts
Create a well-organized document for future reference

Practice t-tests using a statistical package

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Reinforce your understanding of t-tests by working through practical examples.

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Choose a statistical package (e.g., SPSS, SAS, R)
Enter your data into the software
Select the appropriate t-test (e.g., independent samples, paired samples)
Interpret the output (e.g., p-value, confidence intervals)

Create a statistical analysis infographic

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Synthesize your understanding by creating a visual representation of statistical concepts.

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Identify a specific statistical concept to focus on.
Gather data and perform analysis using appropriate statistical methods.
Design an infographic that clearly presents your findings and insights.

Create a poster presentation on a statistical analysis concept

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Deepen your understanding and enhance your communication skills by presenting a statistical concept in a visual format.

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Choose a statistical concept (e.g., p-value, hypothesis testing)
Gather and analyze data
Design and create a poster
Present your poster to peers or faculty

Conduct a small research study using basic statistical methods

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Apply your knowledge and skills to design and conduct a research study, deepening your understanding of medical statistics.

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Identify a research question and develop a study design
Collect and analyze data
Interpret your findings and write a report

Career center

Learners who complete Understanding Clinical Research: Behind the Statistics will develop knowledge and skills that may be useful to these careers:

Biostatistician

As a Biostatistician, you will be responsible for designing, analyzing, and interpreting clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, provides a comprehensive overview of the statistical methods used in clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use. This knowledge is essential for Biostatisticians who want to work in the healthcare industry or in any field that involves clinical research.

See salaries and explore the career path for Biostatistician

Data Analyst

Interpreting clinical research is an essential part of being a Data Analyst, as it allows one to draw meaningful insights from data. This course, Understanding Clinical Research: Behind the Statistics, provides a solid foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use. This knowledge is essential for Data Analysts who want to work in the healthcare industry or in any field that involves analyzing clinical data.

See salaries and explore the career path for Data Analyst

Clinical Research Associate

Clinical Research Associates are responsible for managing clinical research studies. This includes tasks such as recruiting participants, collecting data, and monitoring the progress of the study. This course, Understanding Clinical Research: Behind the Statistics, provides a solid foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use. This knowledge is essential for Clinical Research Associates who want to work in the healthcare industry or in any field that involves clinical research.

See salaries and explore the career path for Clinical Research Associate

Medical Writer

Medical Writers are responsible for writing scientific documents, such as clinical research reports and journal articles. This course, Understanding Clinical Research: Behind the Statistics, provides a solid foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use. This knowledge is essential for Medical Writers who want to work in the healthcare industry or in any field that involves writing about clinical research.

See salaries and explore the career path for Medical Writer

Healthcare Consultant

Healthcare Consultants provide advice to healthcare organizations on a variety of topics, including clinical research. This course, Understanding Clinical Research: Behind the Statistics, provides a solid foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use. This knowledge is essential for Healthcare Consultants who want to work in the healthcare industry or in any field that involves advising on clinical research.

See salaries and explore the career path for Healthcare Consultant

Pharmacist

Pharmacists are responsible for dispensing medications and providing advice on their use. This course, Understanding Clinical Research: Behind the Statistics, provides a solid foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use. This knowledge is essential for Pharmacists who want to work in the healthcare industry or in any field that involves interpreting clinical research.

See salaries and explore the career path for Pharmacist

Epidemiologist

Epidemiologists are responsible for studying the distribution and determinants of health-related states or events in specified populations. As part of their work, they often interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Epidemiologists who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

See salaries and explore the career path for Epidemiologist

Nurse Practitioner

Nurse Practitioners are responsible for providing healthcare services to patients. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Nurse Practitioners who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

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Physician Assistant

Physician Assistants are responsible for providing medical care under the supervision of a physician. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Physician Assistants who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

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Health Policy Analyst

Health Policy Analysts are responsible for analyzing health policy issues. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Health Policy Analysts who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

See salaries and explore the career path for Health Policy Analyst

Healthcare Administrator

Healthcare Administrators are responsible for managing healthcare organizations. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Healthcare Administrators who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

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Public Health Educator

Public Health Educators are responsible for teaching people about health and disease prevention. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Public Health Educators who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

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Healthcare Data Analyst

Healthcare Data Analysts are responsible for analyzing data to improve the quality and efficiency of healthcare services. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Healthcare Data Analysts who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

See salaries and explore the career path for Healthcare Data Analyst

Science Writer

Science Writers are responsible for writing about scientific topics for a general audience. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Science Writers who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

See salaries and explore the career path for Science Writer

Medical Librarian

Medical Librarians are responsible for managing and providing access to medical information. As part of their work, they often review and interpret clinical research studies. This course, Understanding Clinical Research: Behind the Statistics, may be useful for Medical Librarians who want to build a stronger foundation in understanding statistical analysis and the results of clinical research. It covers topics such as study types, describing data, building an intuitive understanding of statistical analysis, hypothesis testing and confidence levels, and which test should you use.

See salaries and explore the career path for Medical Librarian