Quality quandaries: A gentle introduction to Bayesian statistics

Causal Inference in Statistics: A Gentle Introduction

This paper provides a conceptual introduction to causal inference, aimed to assist researchers bene t from recent advances in this area. The paper stresses the paradigmatic shifts that must be undertaken in moving from traditional statistical analysis to causal analysis of multivariate data. Special emphasis is placed on the assumptions that underly all causal inferences, the languages used in ...

A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research

Bayesian statistical methods are becoming ever more popular in applied and fundamental research. In this study a gentle introduction to Bayesian analysis is provided. It is shown under what circumstances it is attractive to use Bayesian estimation, and how to interpret properly the results. First, the ingredients underlying Bayesian methods are introduced using a simplified example. Thereafter,...

Bayes and I: A Gentle Introduction to the Bayesian Approach

Yet, behind the scenes, a very strong assumption—or belief— resides: that there is a fixed single population parameter. In this case, the mean value of weights for teenagers in the city is a single value. Therefore, without a serious flaw in the sampling process, the parameter is constant, though unknown, across all possible samples [2]. However, what if the parameter is not fixed but rather ha...

A gentle introduction to

The PythonTEX package allows authors to combine computational and typesetting tasks by embedding Python code in TEX documents. This package allows access to many powerful Python modules, providing support for such things as symbolic mathematics, plotting, arbitrary precision numerical calculations, and networking. Python’s intuitive syntax, popularity, and extensibility along with TEX’s formatt...

A Gentle Introduction to Tensors