I recently posted about Statistical Inference vs Machine Learning inference vs Deep learning inference. These ideas are key to understanding the mathematical foundations of data science. Its important ...

Happy Wednesday everyone! Most people who know me know that I love Math and Statistics (that’s why I majored in these! 🙂). Today I want to discuss one of my favorite topics in Statistics: Statistical ...

This paper aims to construct a new transformed Weibull distribution model by mathematically transforming the Weibull distribution model. This model significantly enhances its applicability and ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

Confidence intervals are computed from a random sample and therefore they are also random. The long run behavior of a 95% confidence interval is such that we’d expect 95% of the confidence intervals ...

Abstract: The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a ...

How our genes work together to build our cells, organs and bodies, and how mutations in many genes contribute to disease remain fundamental questions in genetics. Despite more than a century of ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...

This module builds on the foundations of statistical inference from MAS1616. Students will know about the distinction between a population and a sample. They will know about the use of estimators ...

Time series is data collected over time, and statistical learning is a field of statistics and machine learning that develops algorithms to model and interpret this data. Together, they use ...