All you need to know about app analytics and user engagement is right here. Read on to learn from the experts.

The danger in comparing your campaign performance against an average
Data Science
June 27, 2017

Performance measurement cannot be viewed in isolation. It becomes meaningful when it is compared against a benchmark. For eg: Metrics

A Marketer’s Guide to A/B Testing
Data Science
April 24, 2017

The primary aim of any marketing campaign is to effectively engage with the target audience and encourage them to perform

The Best Metric to Measure Accuracy of Classification Models
Data Science
November 28, 2016

Unlike evaluating the accuracy of models that predict a continuous or discrete dependent variable like Linear Regression models, evaluating the

A primer on logistic regression – Part I
Data Science
August 8, 2016

In the real world, we often come across scenarios which requires to make decisions that result into finite outcomes, like

A neat trick to increase robustness of regression models
Data Science
August 3, 2016

The first predictive model that an analyst encounters is Linear Regression. A linear regression line has an equation of the

How do we perceive analytics or data science?
Data Science
July 26, 2016

Is the purpose of analytics or data science to draw some insights from data or some cool visualization or is it just a recommendation

The fallacy of seeing patterns
Data Science
July 19, 2016

Human beings try to find patterns to explain the reason behind almost every phenomenon, but that doesn’t mean that there

I wish I had autobots for data transformation
Data Science
June 30, 2016

Being a sci-fi movie buff, I would always wonder if my variables could turn into Autobots just like the movie

A brief primer on linear regression – Part III
Data Science
June 22, 2016

In Part I, we learnt the basics of Linear Regression and in Part II, we have seen that testing the

How to compare apples and oranges ? : Part III
Data Science
June 20, 2016

In the part 1 and part 2 of the series, we looked at ways to compare numerical variables and categorical variables.


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