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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...

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...

Using Central Tendency Measures to Describe Data

The term central tendency refers to some values that tend to describe the centre of the complete data set. There are different measures of central tendency. Each of them give us one single number that attempts to summarise the entire data set within itself. Why do we...

Building Linear Regression Models

What is regression? In the dictionary, the word regression basically means 'to go back'. In terms of statistics too, the meaning is not too different - it means 'to go back to the past data to explain the process that generates the data'. In statistics, a model is a...

Building a Multiple Linear Regression Model

Previously, we have seen situations where an outcome (the dependent variable) is based on a single input variable (independent variable). Sadly, real life is rarely as simple. Most outcomes in real situations are affected by multiple input variables. To...

The Basics

Statistics Stuff

Creating Models with Data