CIND 123 - Data Analytics: Basic Methods
26753
Delivery Options
Online
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Course Description
This 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 or Python.
- 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 or Python.
Notes
*The course will include hands-on labs in Python, and the content will cover both R and Python.
The Azure Virtual Desktop assigned to students will be accessible two days after the course’s starting date, and swapping between sections will not be permitted.
Students will download the Microsoft Remote Desktop app to access the software needed to complete this course’s requirements.
Relevant Programs
- 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 : 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)
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Course Sections