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.
What Will You Learn?
This course provides data analytics technical skills for conducting quantitative analyses on data and big data.
Learn how to:
- Utilize real datasets with graphs and numerical measures.
- Conduct a uni-variate and bi-variate analyses on datasets in R.
- Flag potential outliers for further investigation.
- Illustrate graphically the probability distribution of variables.
- Differentiate between discrete and continuous probability distributions.
- Calculate binomial probabilities using normal approximations.
- Investigate whether a sample size is large enough to apply the central limit theorem.
- Apply testing and estimation techniques for simple linear regression analyses in R.
The deadline to enroll in CIND123 for Spring term is May 2, 2022.
The deadline to enroll in CIND123 for Summer term is June 21, 2022.
Students will also not be allowed to swap between sections of the Data Analytics courses after the above dates.
You must download the Microsoft Remote Desktop in order to access the software needed to complete the requirements for this course. Prior to your first class, you are strongly advised to test the computer you plan to use, as machines operated using a third-party administrator (such as laptops provided by a workplace) may not allow access to the required software/download(s).
International students should use their own virtual private network (VPN) software to connect to University resources.
- Applied Analytics and Statistics for 21st Century Decision-Making : Required Courses (Option 1), Required Courses (Option 2)
- Business Decision Analysis : Electives (select 4)
- Computer Coding (Formerly 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 3)
- Scientific Research Policy and Ethics : Required Courses (select 3)