Writing makes you think - what do you want to communicate, what
point are you trying to make, who are you communicating with? The
act of writing hones mastery, and we believe in communicating information
that is clear, concise and readable. We provide all of our articles
and papers for free, and we aim to provide a distraction-free environment
to learn. While there is an abundance of information in textbooks,
on the internet and in scientific journals, it can be overwhelming to
read complex, complicated documents that are more about the writer's
ego than the reader, or navigate websites that are covered with ads
and distracting gimmicks. We hope you find our articles fun and easy to
read, but most importantly, enlightening.
There is relatively broad range of topics in the articles below, ranging from business analysis to international relations to academic computer science papers, but all have a common theme; using analytical thinking to understand and improve the world around us. Feel free to read any of the papers, ask questions and let us know if you have any comments or suggestions.
'R' is a statistical programming language used by many (if not most) data scientists. Learning to interact with 'R' is an essential skill for data science, although if you have never programmed before, the learning curve can be steep. All of these articles treat learning 'R' in a fun and approachable way.
Statistics is the mathematial foundation for data science - it underlies the entire process, from data collection to accuracy assessment data visualization. These papers approach statistics in an applicable way, focusing on how statistical methodology can be applied to real-world problems in helpful ways.
You're probably heard the buzz around these terms - with the computational power available today, anyone has the ability to quickly and effectively use statistics and machine learning principles to predict and better understand the information that is available. We approach this subject with an enthusiasm of the potential to put them to good use, but they are not magic, and they can only be used effectively on a strong foundation. These papers seek to provide strong insight into the process of building these models, while avoiding sensationalism and over-promises.
We're passionate about using the tools at our disposal to improve the global environment. After several years working on complex, cross-cultural issues in the military, we've found that the same type of analytical thinking in data and computer science can be applied to international affairs, which along with the discipline of history, has traditionally been driven by instinct and cherry-picked information. We approach the subject by finding accurate data and sound reasoning to improve decision-making within global affairs.