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Statistical Decision Theory
This chapter was originally in (Lee, CF, JC Lee and AC Lee, “Statistics for Business and Financial Economics”, Springer, New York 2013.). It...
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Introduction to Bayesian Decision Theory (BDT)
This chapter provides a simple introduction to Bayesian decision theory (BDT) and its core idea: maximising the expectation for utility. We keep the...
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Optimal dichotomization of bimodal Gaussian mixtures
Despite criticism for loss of information and power, dichotomization of variables is still frequently used in social, behavioral, and medical...
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Development in Copula Applications in Forestry and Environmental Sciences
Recently, copula is being used in social, natural, and physical sciences due to its flexibilities in joint distributions and marginals and high...
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Bayesian hierarchical modeling of people’s decision-making during an extreme weather event
Investigating effects of a alarm type on people’s level of fear and protective actions during a tornado event can result in a more effective warning...
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Ivo Molenaar
Ivo Molenaar was professor of statistical analysis and measurement theory for the social sciences at the University of Groningen, and he was...
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Identification of representative trees in random forests based on a new tree-based distance measure
In life sciences, random forests are often used to train predictive models. However, gaining any explanatory insight into the mechanics leading to a...
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Where Are the Social Sciences Going to? The Case of the EU-Funded SSH Research Projects
This article investigates how the emergence of a European research funding affects the directions and processes of scientific knowledge production....
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Convergence of Data Analytics, Big Data, and Machine Learning: Applications, Challenges, and Future Direction
The fusion of Data Analytics, Big Data, and Machine Learning has become a powerful force in the always-changing world of data-driven decision-making....
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On the role of data, statistics and decisions in a pandemic
A pandemic poses particular challenges to decision-making because of the need to continuously adapt decisions to rapidly changing evidence and...
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Introduction
Probability and statistics are two branches of mathematics while probability deals with the laws governing random events, statistics encompasses...
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Bayesian sample size determination for detecting heterogeneity in multi-site replication studies
An ongoing “replication crisis” calls into question scientific discoveries across a variety of disciplines ranging from life to social sciences....
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Internet of Things in Forestry and Environmental Sciences
Internet of Things (IoT) is a revolutionary technology that aims to interconnect everyday objects equipped with identity, sensors, networking, and...
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On reading and interpreting black box deep neural networks
The deep neural networks used in computer vision and in recent large language models are widely recognized as black boxes, a term that describes...
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Neural Networks and Deep Learning
Artificial neural network is a well-known machine learning technique inspired by biological neural network structures. It mimics the human brain’s...
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Ulf Böckenholt
Ulf Böckenholt is the John D. Gray professor of marketing at the Kellogg School of Management at Northwestern University, Illinois. He was president...
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Business Analytics for Managers
Humans are decision-makers. Career and lifestyle decisions such as starting a business, purchasing a product, and investing in the future are all...
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Final Thoughts
The conclusion wrestles with challenges and tradeoffs confronting the application of computational tools to research projects in the humanities and...
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Methodology
Multi-criteria decision-making models (MCDM) are the most widely used decision methods in the sciences, business, government and engineering worlds.
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The Case for a Database Approach
The management of research data in the humanities and social sciences is a genuine, non-trivial challenge from a computational perspective. In this...