In the world of statistical modeling, one powerful approach to account for group differences while understanding overall trends is hierarchical (or multilevel) modeling. This approach allows parameters to vary by groups and captures both within-group and between-group variations. …

In the field of data analysis, we often encounter time series data. From stock prices and weather forecasts to customer demand, these sequential data points indexed in time order carry significant information for various analytical tasks. Bayesian analysis is a powerful statistical technique that allows us to express uncertainty about…

When it comes to advanced statistical analysis and probabilistic modeling, one of the most powerful techniques to emerge in recent years is the Markov Chain Monte Carlo (MCMC) method. Combining the concepts of Monte Carlo simulation and Markov chains, MCMC provides a practical way to perform Bayesian inference on complex…

Let’s consider a hypothetical case where a company is testing two different website designs: Design A and Design B, and wants to determine which one leads to more user conversions. Firstly, we collect our data. For simplicity’s sake, let’s say 1,000 users are shown Design A, with 150 users converting…

Have you ever wondered how you could use probability distributions to understand uncertain events or predict future outcomes? Bayesian analysis provides a powerful framework for doing just this, and PyMC is a Python library that makes implementing Bayesian analysis straightforward and efficient. First, it’s important to understand that Bayesian analysis…

Evidence-based medicine is the “conscientious, explicit, judicious and reasonable use of modern, best evidence in making decisions about the care of individual patients” (Masic I et al. 2008) and has completely transformed the way that medicine is practiced. Patient-centered care is another philosophy of medical care that seeks to focus…

Monte Carlo Estimation Part II At the heart of any Monte Carlo technique, is randomization. We have already learned about the bootstrap technique for estimating a statistical parameter. …

Monte Carlo Estimation Part I — Many digital experiments carried out these days can be happily analyzed using frequentist statistical methods since we expect the data to be normally distributed. However, there are certain metrics that are not so easy. Take, for example, an experiment designed to increase tax collections, or to pay an invoice. If…

Imagine you could build a system that can automatically reach out to users to collect feedback? This is possible today and this blog post will outline how to do it. In this post I will take you through how you build a chatbot using Rasa Open Source. The post was…