Doing Clinical Research: Biostatistics with the Wolfram Language

Go to Course: https://www.coursera.org/learn/clinical-research-biostatistics-wolfram

Introduction

## Course Review: Doing Clinical Research: Biostatistics with the Wolfram Language **Overview** The "Doing Clinical Research: Biostatistics with the Wolfram Language" course on Coursera offers a unique blend of statistical analysis and programming, designed specifically for those in the clinical research field. This course arms you with the essential skills to perform statistical tests, summarize data, and visualize results through practical hands-on learning. Whether you aspire to enhance your research papers, dissertations, or presentations, this course is a powerful stepping stone toward mastering biostatistics. **Why Choose This Course?** The standout feature of this course is its integration of the Wolfram Language, which simplifies the complexities often associated with statistical analysis. The Wolfram Language is known for being intuitive, with built-in knowledge that minimizes the learning curve while providing robust capabilities. Students will benefit from understanding how to conduct statistical analyses that are not just theoretical concepts but practical tools they can use in real-world situations. ### Course Syllabus Breakdown **Week 1: Introduction to the Wolfram Language** The first week sets the stage for the journey ahead. It introduces the motivation behind choosing the Wolfram Language and how it can lead to long-lasting skills in statistical analysis. The course provides insight into acquiring the necessary software, with options for a free, web-based version, making it accessible for everyone—even those without institutional support. **Week 2: Learning to Code** In week two, participants dive into coding basics after familiarizing themselves with the software environment. Starting with simple arithmetic, students gain confidence in coding, which paves the way for more complex data manipulation. This step is crucial as it ensures you can bring your own data into the Wolfram Language for analysis in the coming weeks. **Week 3: Data Analysis and Visualization** This week focuses on summarizing and visualizing data—two essential skills for any researcher. The course teaches participants to convert raw data into meaningful insights through descriptive statistics. The experience of creating visualizations such as scatter plots and box-and-whisker plots is invaluable; the Wolfram Language's customization options empower students to tailor their analyses to specific needs. The optional Honors lessons that introduce machine learning provide an exciting opportunity for those eager to delve deeper. **Week 4: Statistical Testing and Final Project** The concluding week covers critical statistical tests, including Student's t-test and chi-squared tests. Participants will see a practical demonstration project that encapsulates everything learned throughout the course, allowing for a comprehensive review before they tackle the final exam. The option to create a computational essay adds a creative element, catering to those wishing to explore beyond the provided examples. ### Recommended For: - **Graduate Students and Researchers:** If you’re engaged in clinical research or any field requiring biostatistics, this course provides a solid foundation. - **Data Enthusiasts:** Anyone interested in understanding how to summarize and visualize data effectively will find the content beneficial. - **Professionals Seeking Skill Development:** Those looking to enhance their data analysis skills in a user-friendly environment will appreciate the approach offered by the Wolfram Language. ### Conclusion In summary, "Doing Clinical Research: Biostatistics with the Wolfram Language" offers a well-structured curriculum that melds the theoretical concepts of biostatistics with practical implementation skills. The course’s focus on the Wolfram Language is a significant advantage, as it balances ease of learning with powerful analytical capabilities. Whether you are a newcomer to statistical analysis or someone looking to refine your skills, this course is highly recommended, providing you with the tools necessary for success in clinical research and beyond. Consider enrolling to elevate your understanding and proficiency in biostatistics today!

Syllabus

Week 1

This first week establishes the aims of the course and motivation for using the Wolfram Language. We aim to support you in gaining a remarkable new set of skills for doing statistical analysis that you can continue to use long after you complete the course. We will also describe the process of procuring the software that you will use in the course. The first is the absolutely free version, which is software as a service, meaning it runs in any web browser. The second is the desktop version. If you work or study at an institution with a site licence, you will be able to get the software for free. There is also the option to purchase your own licence.

In week 2, we start with some actual coding, now that you know about the Wolfram Language and its different coding environments. We start off with a demonstration of a completed project. It is just a little teaser, showcasing what you will be able to do at the end. Next, we are going to learn to code by doing simple arithmetic. That is simple addition, subtraction, multiplication, and so on. Once you have realized just how simple these tasks are, you will be introduced to the way in which data is stored in a computer language. These are the stepping stone required to bringing in your own data, ready for the analyses in the following weeks.

In week 3, its time to start analyzing data, now that you can write some code and import your data. The two most important steps to understand the message hidden in data, are to summarize and visualize it. Descriptive statistics turn rows and columns of data into something that we as humans can understand. By summarizing values and replacing them with single values, we start to get an idea of what our analyses might show. Visualizing the data is an even better way of getting to grips with data. Box-and-whisker plots, scatter plots, bar charts, and the like are wonderful ways to augment your understanding of the data. The Wolfram Language makes summary statistics easy but it really shines when creating plots. There are almost no limits to customizing plots. No matter what your project requirements, you will learn to create plots that work for you. Starting this week is an optional Honors lessons that introduce machine learning using the Wolfram Language.

This final week covers all the common statistical tests - going from Student's t-test to analysis of variance to chi-squared tests. We conclude the course with a run-through of the demonstration research project that you saw at the beginning of week two. This brings together all the skills that you have acquired during the course and prepares you for the final exam. You will also have the opportunity to create your own computational essay, if you are not content with just working through the demonstration project. For those following the optional Honors lessons there is an introduction to deep learning using the Wolfram Language.