Bringing you into the world of data
In October 2012, the Harvard Business Review published an article calling data science the “sexiest job of the 21st century”, and comparing data scientists with the ubiquitous Wall Street “quants” of the ’80s and ’90s: a data scientist is a… Read moreData Science and Machine Learning
Loosely speaking, a statistic is any function of a sample from the distribution of a random variable; statistics aim to extract information from an observed sample to summarise the essential features of a dataset In general, statistics can be divided… Read moreStatistical Analysis
What can be done with the data, once it has been collected? Two suggestions come to mind: analysis is the process by which we extract actionable insights from the data (this process is discussed in later posts), while visualisation is… Read moreData Visualisation & Representation
Once the raw data has been collected and stored in a dataset that is accessible to data analysts/data scientists, the focus should shift to data cleaning and processing. This requires testing for soundness and fixing errors, designing and implementing strategies… Read moreData Preparation
Data analysis tools and techniques work in conjunction with collected data. The type of data that needs to be collected to carry out such analyses, as well as the priority placed on the collection of quality data relative to other… Read morePrinciples of Data Collection
R has become one of the world’s leading languages for statistical and data analysis. While the base R installation does support simple visualizations, its plots are rarely of high-enough quality for publication. Enter Hadley Wickam’s ggplot2, an aesthetically and logical… Read moreA ggplot2 Primer
What do you feel like eating for dinner tonight? Do you feel like pizza, pasta, or perhaps sushi? When you are asked such a question, you would usually provide (some sort of) answer straight away. But how do you come… Read moreA Short Introduction to Artificial Neural Networks (ANNs)
In Data Science and Data Analysis, as in most technical or quantitative fields of inquiry, there is an important distinction between understanding the theoretical underpinnings of the methods and knowing how and when to best apply them to practical situations…. Read moreData Analysis Case Studies
In his 2006 offering Beautiful Evidence, Edward Tufte highlights what he calls the Fundamental Principles of Analytical Design. In this short article, we illustrate Tufte’s principles by analyzing the Gapminder’s Foundation Health and Wealth 2012 data visualization. Data Science Report Series… Read moreFundamentals Principles of Analytical Design
R has become one of the world’s leading languages for statistical and data analysis. In this report, we provide a short description of its core functionality. Data Science Report Series #1: Basics of R for Data Analysis, by Ehssan Ghashim and… Read moreBasics of R for Data Analysis