Author: Qi Chen

# 1. Introduction

This is the final part of Data Visualization and Analysis with R and Tableau Series, for the previous parts, please refer to part 1/3 and part 2/3 for details.

There are roughly 2 billion people around the world consuming alcoholic drinks. Among them, a great number of people are considered as “binge drinking”, which means consuming 5 or more drinks per single occasion for male and 4 or more drinks for female. Drinking alcohol has caused many problems and there are about 88,000 people died from alcohol-related causes annually. Moreover, \$223.5 billion has been spent for alcohol misuse problems and 75% of the cost are related to binge drinking.… Read more

Author: Qi Chen

# 1. Introduction

In the previous part, we introduced some data visualization techniques and showed the relationship of GDP, healthcare investment and life expectancy grouped by countries. In this article, we will focus on poverty and obesity, and analyze the dataset from United States Department of Agriculture. Specifically, by analyzing the dataset using data visualization techniques, we want to explore the following questions:

1. How does poverty rate vary within racial and ethnic groups?
2. Does the milk/soda price ratio influence obesity rate?
3. Are the obesity and diabetes rates higher in fast paced states like New York States than in agricultural states like Wisconsin?… Read more

Author: Qi Chen

# 1. Introduction

Nowadays, unprecedented volume of data is available from books, radio, television, Internet and so on. From these data, useful knowledge can be discovered. However, data can be in any format such as numbers, text, or sound, which increases the difficulty of discovering useful knowledge. Some data formats, such as numbers, are sometimes too abstract and not friendly to people. As one of the techniques to address this issue, data visualization organizes different formats of data and presents it in a more easily understandable way.

## Panel Discussion on IoT-enabled Data Analytics

We would like to highlight a panel discussion on loT (Internet of Things) – enabled Data Analytics: Opportunities, Challenges and Applications at the INFORMS annual meeting that was held on Nov. 1st – Nov. 4th, in Philadelphia, PA.

In particular, four prestigious panelists joined this session, including Prof. Benoit Montreuil (Georgia Institute of Technology), Prof. George Q. Huang (Hong Kong University), Prof. Soundar Kumara (Penn State University), and Prof. Diego Klabjan (Northwestern University) who all have been the leading scholars in this field. The moderator of this session was Prof. Kaibo Liu (University of Wisconsin – Madison).

The goal of this session is to push the frontier in IoT application and the enabled data analytics research.… Read more

## A Story of Basis and Kernel – Part II: Reproducing Kernel Hilbert Space

Author: Changyue Song

# 1. Opening Words

In the previous blog, the function basis was briefly discussed. We began with viewing a function as an infinite vector, and then defined the inner product of functions. Similar to $\mathcal{R}^n$ space, we can also find orthogonal function basis for a function space.

This blog will move a step further discussing about kernel functions and reproducing kernel Hilbert space (RKHS). Kernel methods have been widely used in a variety of data analysis techniques. The motivation of kernel method arises in mapping a vector in $\mathcal{R}^n$ space as another vector in a feature space.… Read more