In this article, we discuss the basics of ordinal logistic regression and its implementation in R. Ordinal logistic regression is a widely used classification method, with applications in variety of domains. This method is the go-to tool when there is a natural ordering in the dependent variable. For example, dependent ...

I am sure you must have heard of Six Sigma quality standard or Six Sigma experts. But, what is Six Sigma? Six Sigma is a set of techniques used by organizations to improve their processes and optimize operations. Six Sigma was popularized by manufacturing organizations and Jack Welch, former CEO ...

Imagine a situation where you are asked to predict the tourism revenue for a country, let’s say India. In this case, your output or dependent or response variable will be total revenue earned (in USD) in a given year. But, what about independent or predictor variables? You have been ...

The World of Anomalies Imagine you are a credit card selling company and you know about a particular customer who makes a purchase of 25$ every week. You guessed this purchase is his fixed weekly rations but one day, this customer makes a different purchase of 700$. This development will not just ...

Changing Your Viewpoint for Factors In real life, data tends to follow some patterns but the reasons are not apparent right from the start of the data analysis. Taking a common example of a demographics based survey, many people will answer questions in a particular ‘way’. For example, all married ...

Discriminant analysis is used when the variable to be predicted is categorical in nature. This analysis requires that the way to define data points to the respective categories is known which makes it different from cluster analysis where the classification criteria is not know. It works by calculating a score ...

Another way of analysis? When there are so many tools and techniques of prediction modelling, why do we have another field known as survival analysis? As one of the most popular branch of statistics, Survival analysis is a way of prediction at various points in time. This is to say, ...

Imagine you were to buy a car, would you just go to a store and buy the first one that you see? No, right? You usually consult few people around you, take their opinion, add your research to it and then go for the final decision. Let’s take a ...

What is Hierarchical Clustering? Clustering is a technique to club similar data points into one group and separate out dissimilar observations into different groups or clusters. In Hierarchical Clustering, clusters are created such that they have a predetermined ordering i.e. a hierarchy. For example, consider the concept hierarchy of ...

K-Means Clustering is a well known technique based on unsupervised learning. As the name mentions, it forms ‘K’ clusters over the data using mean of the data. Unsupervised algorithms are a class of algorithms one should tread on carefully. Using the wrong algorithm will give completely botched up results and ...

Support Vector Machines (SVM) is a data classification method that separates data using hyperplanes. The concept of SVM is very intuitive and easily understandable. If we have labeled data, SVM can be used to generate multiple separating hyperplanes such that the data space is divided into segments and each segment ...