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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...

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 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...

How to Compute the Measures of Dispersion using Microsoft Excel

Calculating Range in Excel Excel does not offer a function to compute range. However, we can easily compute it by subtracting the minimum value from the maximum value. The formula would be =MAX()-MIN() where the dataset would be the referenced in both the parentheses....

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...

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