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Step-by-step guide on:
How to prepare data sets for analysis
Many businesses come across a lot of data in their day to day operations, and most think they might be able to gain a competitive edge if they just knew what to do with these data.
The very first, and often under estimated task is to prepare a clean data set suitable for visualisation or analysis/prediction purposes. Here we provide a quick guide on how to do this.
Regression is the number one tool you will need for data driven analysis
You likely would have heard of predictive AI analytics, machine learning or data driven decision making. These big words describe different flavours in modern data analytics, but did you know that almost all of them can be framed as regression? Yes, the humble regression model!
The term “regression” dates back to the 19th Century, when Sir Francis Galton first conceived modern notions of correlation and regression. Galton’s interests were in genetics, he initially …
Step by step guide on:
Running and interpreting a linear regression model for non-experts!
Regression models are incredibly powerful and can save you heaps of time trawling through your data. However, unless you are a trained statistician, you might be not so confident in using it.
How to make predictions and interpret the variables? How to assess the quality of the model, and how to diagnose assumptions and when should you care? Our step-by-step guide aim to make it easy for anyone with minimal statistics background to use regression.