Linear Regression is one of the most widely used statistical models. If Y is a continuous variable i.e. can take decimal values, and is expected to have linear relation with X's variables, this relation could be modeled as linear regression, mostly the first model to fit,if we are planning to develop a model of forecasting Y or trying to build hypothesis about relation Xs on Y.
Added by Jishnu Bhattacharya on February 1, 2017 at 8:30pm — No Comments
Most of the articles on extreme events are focusing on the extreme values. Very little has been written about the arrival times of these events. This article fills the gap.
We are interested here in the distribution of arrival times of successive records in a time series, with potential applications to global warming assessment, sport analytics, or high frequency trading. The purpose here is to discover what the distribution of these arrival times is, in absence of any…Continue
This cheat sheet, along with explanations, was first published on DataCamp. Click on the picture to zoom in. To view other cheat sheets (Python, R, Machine Learning, Probability, Visualizations, Deep Learning, Data Science, and so on) click here.
To view a…Continue
Added by Emmanuelle Rieuf on February 1, 2017 at 10:00am — No Comments
Journey Science, being derived from connected data from different customer activities, has become pivotal for the telecommunications industry, providing the means to drastically improve the customer experience and retention. It has the ability to link together scattered pieces of data, and enhance a telco business’s objectives. Siloed…
According to Experian, when it comes to data inaccuracy, much of it is down to human error, in particular, spelling mistakes. The reason for this lies in an over-reliance on manual data entry and the lack of…Continue
Added by Martin Doyle on February 1, 2017 at 5:30am — No Comments