Data Science 101

JANUARY 15, 2020

Bias ( syatematic unfairness in data collection ) can be a potential problem in experiments and we need to take it into account while designing experiments. Some pitfalls of this type of experimentation include: Suppose an experiment is performed to observe the relationship between the snack habit of a person while watching TV.

Experimentation 96

Experimentation Statistics Measurement Testing 96

Occam's Razor

SEPTEMBER 15, 2014

In blue is how much time we spent in 2010 and in blue the time spent in 2014. was the dramatic shift between 2010 to 2014 to mobile content consumption. But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement.

Metrics 141

Metrics Reporting Analytics Marketing 141

Occam's Razor

MARCH 23, 2010

Too many new things are happening too fast and those of us charged with measuring it have to change the wheels while the bicycle is moving at 30 miles per hour (and this bicycle will become a car before we know it – all while it keeps moving, ever faster). . ~ It has simply not had a break to catch a breath and mature. Likely not.

Analytics 118

Analytics Consulting Metrics Experimentation 118

The Unofficial Google Data Science Blog

OCTOBER 12, 2017

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.

Experimentation 61

Experimentation Testing Statistics Metrics 61