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Talking about Quartiles

Quartiles are a frequently used method to split the data and understand the spread. In general, data can be divided in various groupings such that an equal number of points are in each group. Such groups are formed by cutting at specific points called quantiles. If...

The Assumptions in Linear Correlations

Given how simple Karl Pearson's Coefficient of Correlation is, the assumptions behind it are often forgotten. It is important to ensure that the assumptions hold true for your data, else the Pearson's Coefficient may be inappropriate. The assumptions and requirements...

When Things are Correlated, Do they Cause Each Other?

We've talked about how popular the concept of correlation is in business analytics. Causation, and its variants are also used rather commonly. This makes it easy to mistakenly connect the two popular terms and even use them interchangeably. The Latin phrase, cum hoc...

Building Nonlinear Regression Models

We have talked about regression models in the context of linear regression models in the previous post. A nonlinear regression model is one that describes a nonlinear relationship between the dependent and the independent variables. Naturally, the equation of the...

Spearman’s Rank Correlation between Rice and Rainfall

Spearman's Coefficient of Rank Correlation (denoted by rho) is named after the British psychologist, Charles Edward Spearman. Rank correlation is a non-parametric variant of Karl Pearson's Coefficient of Correlation. This means, while Pearson's r requires an...

The Basics

Statistics Stuff

Creating Models with Data