Course Introduction
MATH-7360 Data Analysis
Dr. Xiang Ji @ Tulane University
Aug 19, 2020
Introduction
Course logistics
- Independent project:
- Choose from a pool of subjects (to be provided)
- Analyse your own data
- Present your project on November 18, 20, and 23.
Giant’s shoulders
Previous lecture notes from Dr. Michelle Lacey (Math Department @ Tulane)
Course material from Dr. Hua Zhou (Biostatistics Department @ UCLA)
Various online sources
Statistics and data science
Statistics, the science of data analysis, is the applied mathematics in the 21st century.
Data is increasing in volume, velocity, and variety.
My favorite definition of a data scientist:
A data scientist is someone who is better at statistics than any software engineer and better at software engineering than any statistician.
Big data in 1990s
@Huber94HugeData; @Huber96MassiveData
| Data Size | Bytes | Storage Mode |
|---|---|---|
| tiny | \(10^2\) | piece of paper |
| small | \(10^4\) | a few pieces of paper |
| medium | \(10^6\) (MB) | a floppy disk |
| large | \(10^8\) | hard disk |
| huge | \(10^9\) (GB) | hard disk(s) |
| massive | \(10^{12}\) (TB) | hard disk(s); RAID storage |
A random online cartoon for data scientist
Course description
This course introduces some computing skills and software tools for handling data.
Read syllabus and About the course for a tentative list of topics and course logistics.