STAT 689 – Data Analytics and Visualization

We are pleased to announce a new course offered in the Spring of 2022 – Data Analytics and Visualization being taught by Dr. Derya Akleman (Statistics), Dr. Ann McNamara (Visualization) and Dr. John Keyser (Computer Science & Engineering)

 This course will deliver a comprehensive practical introduction to Data Visualization and Visual Analytics. The teaching team comprises instructors from Visualization, Statistics, and Computer Science to deliver a holistic approach to the development and use of data visualization and analytics tools and methods. The course will use R and RStudio and address the end-to-end process from data collection, through storage and management, to visualization and analysis. The emphasis will be on hands-on practical projects using real-world data. 

 Upon completion of this course, students will be able to do the following: 

Knowledge and understanding 

• Interpret simple R scripts 
• Correctly visualize and summarize basic statistics used in data analysis 
• Define suitable data analysis workflows 
• Evaluate the main variables in the design and prediction 

Competence and skills 

• Use (fundamental) commands in R for data manipulation, statistical tests, and plotting graphs and diagrams 
• Write R code as a script 
• Use and when needed modify existing R scripts 
• Use help pages to understand commands and solve problems 
• Use web resources such as CRAN and Bioconductor to install suitable packages Judgment and approach 
• Design and establish custom approaches for analyzing, visualizing, and interpreting data 
• Translate simple research questions of interest into appropriate R workflows 
• Formulate how R scripts can be created according to the data analysis workflow 
• Assess which factors are important to consider for a well-designed experiment 

Prerequisites:

Stat 604

Credits: 3

Check out our Courses page for the full list.