Course DescriptionThis course is an introduction to R, analyzing and exploring data with R, and using R with a database. It focuses on statistics for model building and evaluation. Topics cover experimental research, correlation analysis, regression, confidence intervals, and group comparisons, and parametric and non-parametric models.
In-class course delivery and on-site computer labs and video lectures
The course meets once a week on campus for an in-class session. These weekly in-class sessions on campus are held in a computer lab and run from 6:30 p.m. to 9:30 p.m.
Students have facilitated in-class computer lab time and open computer lab hours on Ryerson campus.
Computer Requirements: Students in the Data Analytics, Big Data, and Predictive Analytics certificate should consult the attached flyer for computer requirements.
Throughout the semester, student questions related to course content may be answered either by the instructor on discussion board or by an online tutor via email. For more information, please email Anne-Marie Brinsmead, Program Director, at email@example.com
- Applied Analytics and Statistics for 21st Century Decision-Making : Required Courses (Option 1), Required Courses (Option 2)
- Business Decision Analysis : Electives (select 4)
- Computer Programming Applications : Electives (select 2)
- Data Analytics, Big Data, and Predictive Analytics : Required Courses
- Financial Predictive Data Analytics : Electives (select 2)
- Health Informatics : Electives (select 4)
- Scientific Research Policy and Ethics : Required Courses (select 3)