---
title: "Course Introduction"
author: "Dr. Hua Zhou"
date: "Jan 9, 2018"
output:
  ioslides_presentation: default
subtitle: Biostat M280
bibliography: ../bib-HZ.bib
csl: ../apa.csl
---
<!-- I could not get R Markdown's citations to work as the works cited at the
  end would not continue onto multiple slides.  If you know how to fix that, 
  please let me know. -->
$\DeclareMathOperator*{\argmin}{arg\,min}$

# What is this course about?

## Statistics and data science

- This course (Biostat M280) is used as a placeholder for _Biostat 203B: Introduction to Data Science_, which is pending approval.

- Statistics, the science of _data analysis_, is the applied mathematics in the 21st century.

- Data is increasing in [volume, velocity, and variety](http://www.forbes.com/sites/oreillymedia/2012/01/19/volume-velocity-variety-what-you-need-to-know-about-big-data/).

## Classification of data sets by @Huber94HugeData; -@Huber96MassiveData {.smaller}

| 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 |


## Four V's of big data

<p align="center">
  <img src="./4-Vs-of-big-data.jpg" height="450" width="700">
</p>
Source: [IBM](http://www.ibmbigdatahub.com/infographic/four-vs-big-data).

## Course desciption

- This course introduces some computing skills and software tools for handling potentially big public health data.

- Read [syllabus](http://hua-zhou.github.io/teaching/biostatm280-2018winter/syllabus.html) for a tentative list of topics and course logistics.

## References

