Data Technologies for Statistical Analysis
Spring 2023
TR 2:10 - 3:25 pm, Lagomarcino 1445, see zoom link in Canvas
Office Hours: by appointment
Instructor: Heike Hofmann, hofmann at iastate dot edu
TA: Ganesh Krishnan, ganeshk at iastate dot edu
Course description:
Not all data lives in nice, clean spreadsheets, not all data fits in a computer’s main memory. As statisticians we cannot always rely on other people and sciences to get the data into formats that we can deal with: we will discuss aspects of statistical computing as they are relevant for data analysis. Read and work with data in different formats: flat files, databases, web technologies. Elements of literate programming help us with making our workflow transparent and analyses reproducible. We will discuss communication of results in form of R packages and interactive web applications.
Learn how to…
- read and combine data from flat files, SQL database, binary netCDF, and making use of web technologies as data source.
- compute with data.
- clean the data, check the quality, impute missing values.
- write efficient and reproducible code so others are able to replicate the analysis.
- develop software, individually and collaboratively, debug, profile and package R code.
- experiment with event driven programming to build an interactive graphic, and a GUI.
- pull data together to solve a contemporary problem.
More info…
Use the navigation bar above!
The course organization on GitHub: https://github.com/stat585-at-ISU
Repo that creates this website: https://github.com/Stat585-at-ISU/Stat585-at-ISU.github.io