# statistics

### Performing Nonlinear Least Square and Nonlinear Regressions in R

Linear regression is a basic tool. It works on the assumption that there exists a linear relationship between the dependent and independent variable, also known as the explanatory variables and output. However, not all problems have such a linear relationship. In fact, many of the problems we see today are

### The Problem With (Statistical) False Friends

I recently stumbled across a research paper, Using Deep Learning and Google Street View to Estimate the Demographic Makeup of the US, which piqued my interest in derivative uses of data, an ongoing research interest of mine. A variety of deep learning techniques were used to draw conclusions about relationships

### The Mathematics of Machine Learning

In the last few months, I have had several people contact me about their enthusiasm for venturing into the world of data science and using Machine Learning (ML) techniques to probe statistical regularities and build impeccable data-driven products. However, I’ve observed that some actually lack the necessary mathematical intuition and

### Get the facts straight: The 10 Most Common Statistical Blunders

Competent analysis is not only about understanding statistics, but about implementing the correct statistical approach or method. In this brief article I will showcase some common statistical blunders that we generally make and how to avoid them. To make this information simple and consumable I have divided these errors into

### “Being comfortable with ambiguity and successfully framing problems is a great way to differentiate yourself” – Interview with Stitch Fix’s Brad Klingenberg

Brad Klingenberg is the Director of Styling Algorithms at Stitch Fix in San Francisco. His team uses data and algorithms to improve the selection of merchandise sent to clients. Prior to joining Stitch Fix Brad worked with data and predictive analytics at financial and technology companies. He studied applied mathematics

### “Playing in Everyone’s Back Yard” – An Interview with Data Scientist David Hand

David Hand is Senior Research Investigator and Emeritus Professor of Mathematics at Imperial College, London, and Chief Scientific Advisor to Winton Capital Management. He is a Fellow of the British Academy, and a recipient of the Guy Medal of the Royal Statistical Society. He has served (twice) as President of

### Unemployment & Inflation Data from the Eurozone Suggests We’re Turning a Corner

Recent data gathered by data mining firms and governing authorities in Europe has revealed the current unemployment and inflation situation in Eurozone, and things might just be looking up for the hard hit. Key elements of Eurozone’s findings, as The Guardian pointed out, are: Statistics provided by Eurostat show that

### 7 Ways Data Scientists use Statistics

William is a Data scientist at Quora, interested in data-driven decision making to improve both product and business. Always interested in learning new things and exploring the ubiquity of data in everyday life. 1. Design and interpret experiments to inform product decisions Observation: Advertisement variant A has a 5% higher

### Predicting Deaths in Game of Thrones With Statistical Modelling

Who Will Be the Next Character to Die in Game of Thrones? It’s a question that is likely to have been brought up in your social circle at some point in the last couple of years – and a perfect opportunity to arm yourself with predictive analytics. Richard Vale, a

### Simpson’s Paradox in Mobile App Monetization

Simpson’s paradox happens when behaviour at the group level is different from the behaviour of its subgroups. For example, consider a mobile app with 10,000 Android users and 5,000 on iOS. If we make the assumption that all users spend equally, then it may make more sense to prioritize development