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
There’s a great deal of open data available on the GoC Open Data Portal. To have some fun, I’ve decided to randomly select datasets from the portal and explore what can be learned from these datasets using some quick analysis… Read moreDiving in to GoC Open Data – A CRTC dataset
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