We may earn an affiliate commission when you visit our partners.
Kate Sandars,
Chris Wild,
and
Mike Forster
Topics Covered
- Data and its organisation
- Basic statistics
- Making discoveries working with several variables simultaneously
- Sources of error and misconception
- Confidence intervals
- Statistical tests via randomisation
- Seasonal decomposition and forecasting
Register for this course and see more details by visiting:
OpenCourser.com/course/6dchw6/data
Save this course
Save Data to Insight: An Introduction to Data Analysis and Visualisation to your list so you can find it easily later:
Save
Save
Reviews summary
Solid introduction to data analysis concepts
This course covers the basics of data analysis and visualization. It is suitable for beginners and those who want a refresher. The course is well-structured and paced, and the content is delivered in a clear and concise manner. However, it does not teach any proficiency in the actual programming of R.
Activities
Coming soon
We're preparing activities for
Data to Insight: An Introduction to Data Analysis and Visualisation.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Data to Insight: An Introduction to Data Analysis and Visualisation will develop knowledge and skills
that may be useful to these careers:
For more career information including salaries, visit:
OpenCourser.com/course/6dchw6/data
Reading list
We haven't picked any books for this reading list yet.
Comprehensive textbook on database systems. It covers a wide range of topics, including data modeling, database design, and query processing. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Save
Comprehensive guide to data warehousing. It covers a wide range of topics, including data modeling, data integration, and data analysis. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Practical guide to big data analytics. It covers a wide range of topics, including data exploration, data mining, and machine learning. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Provides a comprehensive overview of algorithm design techniques. It covers a wide range of topics, including sorting, searching, and graph traversal. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Provides a comprehensive overview of data structures and algorithms in Java. It covers a wide range of topics, including sorting, searching, and graph traversal. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Provides a comprehensive overview of data structures and algorithms in R. It covers a wide range of topics, including sorting, searching, and graph traversal. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Provides a comprehensive overview of data structures and algorithms in Scala. It covers a wide range of topics, including sorting, searching, and graph traversal. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Provides a comprehensive overview of data structures and algorithms in Go. It covers a wide range of topics, including sorting, searching, and graph traversal. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Provides a comprehensive overview of data structures and algorithms in Julia. It covers a wide range of topics, including sorting, searching, and graph traversal. The book is written in a clear and concise style, and it is well-suited for both students and practitioners.
Is written specifically for psychology students and researchers and covers a wide range of statistical methods, from descriptive statistics to advanced multivariate techniques.
A popular introductory statistics textbook that covers a wide range of topics, from data collection to statistical inference.
Save
Provides a comprehensive overview of statistical methods, from the basics to advanced topics.
Save
This open-source textbook provides a comprehensive introduction to statistics, including interactive simulations and exercises.
Provides a mathematical introduction to statistical theory, including topics such as probability, estimation, and hypothesis testing.
Provides a comprehensive overview of statistical methods in French, covering a wide range of topics from data collection to statistical inference.
Provides a comprehensive overview of statistical methods in Spanish, covering a wide range of topics from data collection to statistical inference.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/6dchw6/data
Share
Similar courses
Here are nine courses similar to
Data to Insight: An Introduction to Data Analysis and Visualisation.
Introduction to Cognitive Psychology: An Experimental Science
OpenCourser.com/course/mazyhi/introduction
Introduction to Cognitive Psychology: An Experimental...
Introduction to Big Data
OpenCourser.com/course/0kjs82/introduction
Introduction to Big Data
How to Succeed at: Interviews
OpenCourser.com/course/zxfqgj/how
How to Succeed at: Interviews
Hurricane Tracking with Satellite Data
OpenCourser.com/course/lbfw55/hurricane
Hurricane Tracking with Satellite Data
Introduction to Humanitarian Aid
OpenCourser.com/course/ee04rl/introduction
Introduction to Humanitarian Aid
Programming 103: Saving and Structuring Data
OpenCourser.com/course/4ntjth/programming
Programming 103: Saving and Structuring Data
From Crime to Punishment: an Introduction to Criminal Justice
OpenCourser.com/course/h1jtib/from
From Crime to Punishment: an Introduction to Criminal...
Data Science for Environmental Modelling and Renewables
OpenCourser.com/course/32yc21/data
Data Science for Environmental Modelling and Renewables
Big Data Analytics: Opportunities, Challenges and the Future
OpenCourser.com/course/ruul35/big
Big Data Analytics: Opportunities, Challenges and the...
Our mission
OpenCourser helps millions of learners each year. People visit us to learn workspace skills, ace their exams, and nurture their curiosity.
Our extensive catalog contains over 50,000 courses and twice as many books. Browse by search, by topic, or even by career interests. We'll match you to the right resources quickly.
Find this site helpful? Tell a friend about us.
Affiliate disclosure
We're supported by our community of learners. When you purchase or subscribe to courses and programs or purchase books, we may earn a commission from our partners.
Your purchases help us maintain our catalog and keep our servers humming without ads.
Thank you for supporting OpenCourser.
© 2016 - 2024 OpenCourser