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Juan H Klopper
This course aims to empower you to do statistical tests, ready for incorporation into your dissertations, research papers, and presentations. The ability to summarize data, create plots and charts, and to do the statistical tests that you commonly see in the literature is a powerful skill indeed.
There are powerful tools readily available to achieve these goals. None are quite as easy to learn, yet as powerful to use, as the Wolfram Language. Knowledge is literally built into the language. With its well-structured and consistent approach to creating code, you will become an expert in no time.
Read more
This course aims to empower you to do statistical tests, ready for incorporation into your dissertations, research papers, and presentations. The ability to summarize data, create plots and charts, and to do the statistical tests that you commonly see in the literature is a powerful skill indeed.
There are powerful tools readily available to achieve these goals. None are quite as easy to learn, yet as powerful to use, as the Wolfram Language. Knowledge is literally built into the language. With its well-structured and consistent approach to creating code, you will become an expert in no time.
Read more
This course aims to empower you to do statistical tests, ready for incorporation into your dissertations, research papers, and presentations. The ability to summarize data, create plots and charts, and to do the statistical tests that you commonly see in the literature is a powerful skill indeed.
There are powerful tools readily available to achieve these goals. None are quite as easy to learn, yet as powerful to use, as the Wolfram Language. Knowledge is literally built into the language. With its well-structured and consistent approach to creating code, you will become an expert in no time.
This course follows the approach of learning statistical analysis through the use of a computer language. It requires no prior knowledge of coding. An exciting journey awaits. If you want even more, there are optional Honors lessons on machine learning that cover the support in the Wolfram Language for deep learning.
Register for this course and see more details by visiting:
OpenCourser.com/course/xycsx5/doing
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What's inside
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.
Read more
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.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
An ideal fit for academics who need statistical analysis methods for their research papers
Develops statistical analysis skills using the powerful and easy-to-learn Wolfram Language
Offers optional lessons on machine learning for those seeking to expand their knowledge
This course has the potential to elevate your research and presentations through robust statistical analysis
Provides hands-on training by guiding you through real-world statistical analysis projects
Save this course
Create your own learning path.
Save this course to your list so you can find it easily later.
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Reviews summary
Biostatistics in clinical research with wolfram
According to learners, this course offers a solid introduction to conducting biostatistical analyses in clinical research using the Wolfram Language. Many highlight the surprising ease of learning the Wolfram Language, even for those with no prior coding experience, finding it intuitive for statistical tasks. The course is praised for providing practical, immediately applicable skills covering descriptive statistics and common tests needed for research. While broadly positive, some reviewers noted that more complex statistical topics could benefit from deeper exploration, and a few encountered minor initial hurdles with software setup or specific syntax elements. Overall, it's seen as a highly relevant course for researchers seeking a powerful, accessible statistical tool.
Instructor is clear and engaging.
"The instructor's explanations were consistently clear and easy to follow, even for complex topics."
"I found the lectures engaging and the way concepts were presented made sense."
"Very happy with the clarity of the teaching throughout the modules."
"The explanations provided made learning both biostatistics and the Wolfram Language straightforward."
"Appreciate how well the material was explained."
Covers key statistical tests.
"The course covers all the essential statistical tests commonly used in clinical research, which was exactly what I needed."
"From descriptive stats to t-tests and ANOVA, the course covers the core methods well."
"I feel equipped to perform the statistical analyses I typically encounter in literature after completing this."
"Good overview of the most important statistical procedures required for research papers."
"Provides a solid foundation in the necessary biostatistical methods using the language."
Surprisingly easy for coding beginners.
"As someone with no prior coding knowledge, I found the Wolfram Language surprisingly easy to pick up through this course's guidance."
"They really make the Wolfram syntax accessible; it wasn't as daunting as I expected for statistical programming."
"I had zero experience with programming, but the step-by-step approach made learning Wolfram for biostatistics manageable."
"The course successfully showed that you don't need to be a programmer to do statistical analysis with Wolfram."
"Easier to grasp than other statistical software I've attempted to learn."
Learn practical use of Wolfram Language.
"This course provided practical examples using the Wolfram Language that I could directly apply to my clinical data."
"The way it demonstrates statistical tests within the Wolfram environment is incredibly useful for real research work."
"I appreciated learning how to use a powerful tool like Wolfram for my specific biostatistics needs in the lab."
"Applying the language to actual statistical problems felt very hands-on and relevant."
"It gave me the confidence to start analyzing my own research data using the methods taught."
Minor hurdles with software.
"Had a little trouble with the initial software setup, but it was resolved."
"Getting used to the specific environment and some function calls took a moment."
"While the language is easy, navigating the documentation or finding the right command was occasionally tricky."
"Minor issues encountered when working with specific data formats in Wolfram."
"Setup wasn't completely seamless for everyone in my group."
Could use more depth in some areas.
"While it covers the basics well, I felt some more complex statistical concepts could have been explored in greater depth."
"It's a great introduction, but you might need supplementary material for truly advanced biostatistical techniques."
"Wish they had gone into a bit more detail on topics like regression or survival analysis."
"Focuses primarily on standard tests; less common or more advanced methods are not covered thoroughly."
"Good starting point, but don't expect it to be your only resource for advanced biostatistics."
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 Doing Clinical Research: Biostatistics with the Wolfram Language with these
activities:
Review the book 'Introductory Statistics with R' by Peter Bruce
Show steps
Reading this book will provide you with a solid foundation in statistical concepts and R programming.
View
Machine Learning for Business Analytics:...
on Amazon
Show steps
-
Read the chapters relevant to the topics covered in the course.
-
Work through the practice exercises at the end of each chapter.
-
Use the book as a reference during the course for further clarification.
Refresh your high school Algebra fundamentals
Show steps
Practicing essential pre-requisite Algebra skills can enhance your comprehension and success rate in this course.
Browse courses on
Algebra
Show steps
-
Review your course notes or textbooks.
-
Take a practice quiz or test to identify areas that need improvement.
-
Seek help from a tutor or online resources if needed.
Follow online tutorials on statistical analysis
Show steps
Watching and following along with guided tutorials will help you grasp complex statistical concepts more easily and at your own pace.
Browse courses on
Statistical Analysis
Show steps
-
Search for reputable online tutorials on statistical analysis.
-
Choose tutorials that cover the topics you need to reinforce.
-
Take notes and practice the concepts demonstrated in the tutorials.
-
Share your insights and ask questions in online forums related to the tutorials.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice coding challenges and exercises
Show steps
Regular practice with coding problems will help you develop your programming skills and prepare you for the course's assignments.
Browse courses on
Coding Challenges
Show steps
-
Find online coding challenges or exercises.
-
Set aside time each week to practice solving these challenges.
-
Review your solutions and identify areas for improvement.
-
Seek help from online forums or mentors if you get stuck.
Join a study group or discussion forum
Show steps
Engaging with peers in a study group or discussion forum can enhance your understanding through shared perspectives and collaborative problem-solving.
Show steps
-
Find or create a study group with classmates or online.
-
Set regular meeting times to discuss course material.
-
Collaborate on assignments and projects.
Attend a workshop on statistical software
Show steps
Attending a workshop will provide you with structured guidance, hands-on practice, and opportunities to interact with experts in statistical software.
Browse courses on
Statistical Software
Show steps
-
Research and identify workshops related to statistical software.
-
Register for a workshop that aligns with your interests and learning goals.
-
Attend the workshop and actively participate in the activities and discussions.
Create a data visualization project
Show steps
Working on a data visualization project will provide you with hands-on experience applying the concepts learned in this course and enhance your portfolio.
Browse courses on
Data Visualization
Show steps
-
Choose a dataset and define your visualization goals.
-
Select appropriate visualization techniques and tools.
-
Create your visualization and analyze the results.
-
Present your project to others for feedback.
Write a blog post or article on a statistical topic
Show steps
Writing about statistical concepts will help you solidify your understanding, improve your communication skills, and contribute to the broader learning community.
Browse courses on
Statistical Analysis
Show steps
-
Choose a statistical topic that interests you and aligns with the course content.
-
Research and gather information from credible sources.
-
Organize your thoughts and write a well-structured post or article.
-
Publish your writing on a blog or online platform.
Review the book 'Introductory Statistics with R' by Peter Bruce
Show steps
Reading this book will provide you with a solid foundation in statistical concepts and R programming.
View
Machine Learning for Business Analytics:...
on Amazon
Show steps
Show steps
Show steps
- Read the chapters relevant to the topics covered in the course.
- Work through the practice exercises at the end of each chapter.
- Use the book as a reference during the course for further clarification.
Refresh your high school Algebra fundamentals
Show steps
Practicing essential pre-requisite Algebra skills can enhance your comprehension and success rate in this course.
Browse courses on
Algebra
Show steps
Show steps
Show steps
- Review your course notes or textbooks.
- Take a practice quiz or test to identify areas that need improvement.
- Seek help from a tutor or online resources if needed.
Follow online tutorials on statistical analysis
Show steps
Watching and following along with guided tutorials will help you grasp complex statistical concepts more easily and at your own pace.
Browse courses on
Statistical Analysis
Show steps
Show steps
Show steps
- Search for reputable online tutorials on statistical analysis.
- Choose tutorials that cover the topics you need to reinforce.
- Take notes and practice the concepts demonstrated in the tutorials.
- Share your insights and ask questions in online forums related to the tutorials.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice coding challenges and exercises
Show steps
Regular practice with coding problems will help you develop your programming skills and prepare you for the course's assignments.
Browse courses on
Coding Challenges
Show steps
Show steps
Show steps
- Find online coding challenges or exercises.
- Set aside time each week to practice solving these challenges.
- Review your solutions and identify areas for improvement.
- Seek help from online forums or mentors if you get stuck.
Join a study group or discussion forum
Show steps
Engaging with peers in a study group or discussion forum can enhance your understanding through shared perspectives and collaborative problem-solving.
Show steps
Show steps
Show steps
- Find or create a study group with classmates or online.
- Set regular meeting times to discuss course material.
- Collaborate on assignments and projects.
Attend a workshop on statistical software
Show steps
Attending a workshop will provide you with structured guidance, hands-on practice, and opportunities to interact with experts in statistical software.
Browse courses on
Statistical Software
Show steps
Show steps
Show steps
- Research and identify workshops related to statistical software.
- Register for a workshop that aligns with your interests and learning goals.
- Attend the workshop and actively participate in the activities and discussions.
Create a data visualization project
Show steps
Working on a data visualization project will provide you with hands-on experience applying the concepts learned in this course and enhance your portfolio.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a dataset and define your visualization goals.
- Select appropriate visualization techniques and tools.
- Create your visualization and analyze the results.
- Present your project to others for feedback.
Write a blog post or article on a statistical topic
Show steps
Writing about statistical concepts will help you solidify your understanding, improve your communication skills, and contribute to the broader learning community.
Browse courses on
Statistical Analysis
Show steps
Show steps
Show steps
- Choose a statistical topic that interests you and aligns with the course content.
- Research and gather information from credible sources.
- Organize your thoughts and write a well-structured post or article.
- Publish your writing on a blog or online platform.
Career center
Learners who complete Doing Clinical Research: Biostatistics with the Wolfram Language will develop knowledge and skills
that may be useful to these careers:
Statistician
Statistician
Statisticians apply mathematical and statistical techniques to collect, analyze, interpret, and present data. They work in a variety of industries, including healthcare, finance, and government. This course can help you develop the skills you need to be a successful statistician, including data analysis, statistical modeling, and data visualization.
Data Analyst
Data Analyst
Data analysts use data to solve business problems. They work in a variety of industries, including healthcare, finance, and retail. This course can help you develop the skills you need to be a successful data analyst, including data cleaning, data analysis, and data visualization.
Data Scientist
Data Scientist
Data scientists use data to build models that can predict future events. They work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to be a successful data scientist, including data mining, machine learning, and artificial intelligence.
Machine Learning Engineer
Machine Learning Engineer
Machine learning engineers build and maintain machine learning models. They work in a variety of industries, including healthcare, finance, and transportation. This course can help you develop the skills you need to be a successful machine learning engineer, including data engineering, machine learning, and deep learning.
Business Analyst
Business Analyst
Business analysts use data to help businesses make better decisions. They work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to be a successful business analyst, including data analysis, data visualization, and project management.
Financial Analyst
Financial Analyst
Financial analysts use data to make investment decisions. They work in a variety of industries, including investment banking, asset management, and hedge funds. This course can help you develop the skills you need to be a successful financial analyst, including data analysis, financial modeling, and valuation.
Market Researcher
Market Researcher
Market researchers use data to understand consumer behavior. They work in a variety of industries, including marketing, advertising, and product development. This course can help you develop the skills you need to be a successful market researcher, including data collection, data analysis, and data visualization.
Operations Research Analyst
Operations Research Analyst
Operations research analysts use data to improve the efficiency of business operations. They work in a variety of industries, including manufacturing, logistics, and healthcare. This course can help you develop the skills you need to be a successful operations research analyst, including data analysis, optimization, and simulation.
Risk Analyst
Risk Analyst
Risk analysts use data to identify and assess risks. They work in a variety of industries, including insurance, finance, and healthcare. This course can help you develop the skills you need to be a successful risk analyst, including data analysis, risk modeling, and risk management.
Software Engineer
Software Engineer
Software engineers design, develop, and maintain software applications. They work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to be a successful software engineer, including programming, data structures, and algorithms.
Quantitative Analyst
Quantitative Analyst
Quantitative analysts use data to develop trading strategies. They work in a variety of industries, including investment banking, asset management, and hedge funds. This course can help you develop the skills you need to be a successful quantitative analyst, including data analysis, financial modeling, and machine learning.
Actuary
Actuary
Actuaries use data to assess risk and uncertainty. They work in a variety of industries, including insurance, finance, and healthcare. This course can help you develop the skills you need to be a successful actuary, including data analysis, risk modeling, and financial mathematics.
Data Engineer
Data Engineer
Data engineers build and maintain data pipelines. They work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to be a successful data engineer, including data engineering, data warehousing, and data mining.
Database Administrator
Database Administrator
Database administrators design, implement, and maintain databases. They work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to be a successful database administrator, including database design, database administration, and data security.
Information Security Analyst
Information Security Analyst
Information security analysts protect computer systems and networks from unauthorized access. They work in a variety of industries, including healthcare, finance, and manufacturing. This course can help you develop the skills you need to be a successful information security analyst, including data security, network security, and risk management.
For more career information including salaries, visit:
OpenCourser.com/course/xycsx5/doing
Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Doing Clinical Research: Biostatistics with the Wolfram Language.
Provides a comprehensive overview of artificial intelligence in healthcare. It valuable resource for students and researchers who are interested in learning about artificial intelligence.
Provides a comprehensive overview of the elements of statistical learning. It valuable resource for students and researchers who need to learn about statistical learning.
Provides a comprehensive overview of biostatistical methods. It valuable resource for students and researchers who need a strong foundation in biostatistics.
Provides a comprehensive overview of clinical research design and statistical analysis. It valuable resource for anyone involved in the design, conduct, or analysis of clinical trials.
Provides a comprehensive overview of statistical models for biomedical research. It valuable resource for anyone involved in the design, conduct, or analysis of clinical trials.
Provides a comprehensive overview of Python for data analysis. It valuable resource for students and researchers who need to learn about Python.
Save
Provides a comprehensive overview of R for data science. It valuable resource for students and researchers who need to learn about R.
Classic text on statistical methods in clinical research, providing a comprehensive overview of the topic. It valuable reference for anyone involved in the design, conduct, or analysis of clinical trials.
Provides a comprehensive overview of regression modeling strategies. It valuable resource for students and researchers who need to learn about regression modeling.
Popular textbook for introductory statistics courses. It provides a clear and concise introduction to the basic concepts of statistics.
Is an excellent resource for students who are new to statistics. It provides a clear and concise introduction to the basic concepts of statistics.
Provides a clear and concise introduction to biostatistics. It valuable resource for students and researchers who are new to the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/xycsx5/doing
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Rating
4.7
Effort
15 hours to complete
Level
Introductory
Via
Coursera
Institution
University of Cape Town
Instructor
Juan H Klopper
Language
English
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