Data is everywhere and so much of it is unexplored. Learn how to investigate and summarize data sets using R and eventually create your own analysis.
Type of Material:
Online Course
Recommended Uses:
It is a self-contained course on data analysis using R.
Technical Requirements:
Web browser
Identify Major Learning Goals:
Upon completion of this course, students will be able to:
1. explain the idea of data analytics;
2. describe the statistical theories and techniques in data analysis;
3. apply different techniques in R to summarize/analyse data;
Target Student Population:
Graduate School, College high;
Prerequisite Knowledge or Skills:
Basic programming skills; high school mathematics;
Content Quality
Rating:
Strengths:
It covers quite a large area of data analytics using R.
For the installation of RStudio, it covers both Windows and Mac platforms and explains the details of the use of the panels on the layout.
The knowledge covered in this course is two-fold. Firstly it covers the foundamental concepts in statistics for exploring data. Secondly, it cover the programming techniques in R. The content is quite complete and comprehensive. Students should be able to apply the knowledge to analyze their data after this course.
Concerns:
The course mainly covers the basic knowledge. Students need to find other resources if they want to go beyond the basis.
Potential Effectiveness as a Teaching Tool
Rating:
Strengths:
At starting of each lesson, the introductory video gives good summary of the content and learning objectives.
In addition to the screen captures showing to do EDA using R, the course also provides some interviews with experts or users of R to present the actual use cases of EDA.
It also comes with some links to the relevant materials over the Internet, which are quite useful.
As a self-pacing course, the learners can decide the progress and keep track of the individual progress.
In summary, the learning goals and the pre-requisite knowledge are very clear. THe instruction is very clear. Students should be able to grasp the knowledge and start exploring data using R. The content is very suitable for beginners in data analytics and those who are new to R.
Ease of Use for Both Students and Faculty
Rating:
Strengths:
Throughout the course, the exercises provided can be done directly on the page and the interface shown is easy to use.
The quizzes provide both close-ended and open-ended questions. The closed ended given instant responses, but it maybe frustrating when one or two answers getting wrong in a question with eight answer boxes and the response is just "Try again". For the open-ended, it would be more impressive if some common answers and some feedbacks are also given.
In summary, the course is very easy to follow. It contains video instruction and illustration. The quizzes are effective for self-assessment. There is a final project at the end, so that students can consolidate the knowledge in the course.
Creative Commons:
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