Statistics

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When Data Lies: Simpson’s Paradox–A Step-by-Step Simulation Code Notebook

Find the RMarkdown Notebook on Github and Run the Code Yourself! Introduction: A Medical Mystery Imagine you’re analyzing data from a clinical trial testing a new treatment. You run a…
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Welch’s T-Test for Unequal Variances–A Tutorial With Coding Notebook

Get accces to our free Github Notebook Library to download this code notebook and try for yourself! Welch’s correction is used to account for unequal variances when we test equality…
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Epidemiology vs Biostatistics – A Comprehensive Career & Education Guide

Introduction Public health is a collaborative field where diverse professionals work together to solve complex health challenges. Two of the most vital players in this space are epidemiologists and biostatisticians.…
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Healthcare AI – The Importance of Real-World Data

The future of AI in healthcare relies on the technology’s ability to process vast amounts of real-world data (RWD), with the goal of improving patient management and outcomes. Novel AI…
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Causal Modeling Helps Machine Learning Find Better Drug Targets

In a continuously evolving drug discovery field, finding potential drug targets efficiently and effectively is an ongoing challenge. Artificial intelligence and machine learning have enabled drug discovery using a data-driven…
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Educational and Career Resources in Public Health: A Comprehensive Guide

Introduction In an era defined by global health crises, data-driven decision-making has never been more essential. At the heart of this transformation lies biostatistics: a foundational discipline that empowers public…
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Epidemiology vs. Biostatistics: What is the Difference? – A Comprehensive Guide

Introduction Epidemiology and biostatistics are two fundamental disciplines in public health research, often working in tandem to analyze health-related data and improve population well-being. While they share common objectives, their…
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Biostatistics in Public Health: Principles, Methods, and Case-Studies – A Comprehensive Guide

Introduction Public health depends on data-driven decisions to improve outcomes and prevent disease, and biostatistics is a vital tool in this effort. By applying statistical methods to health data, biostatistics…
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Parametric Modeling of Failure Time Data in Time-to-Event (or Survival) Analysis: Part II

This article is part of an extended series of tutorials for time-to-event (or survival) analysis. The next article is here. Introduction This is the second part of the article on…
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Parametric Modeling of Failure Time Data in Time-to-Event (or Survival) Analysis

This article is part of an extended series of tutorials for time-to-event (or survival) analysis. The next article is here. Introduction The four previous articles that I wrote were based…
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Statistical Hypothesis Testing of Failure-Time Data in Time-to-Event (or Survival) Analysis (Part II)

This article is part of an extended series of tutorials for time-to-event (or survival) analysis. The next article is here. Introduction This article is a continuation of the series of…
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Statistical Hypothesis Testing of Failure-Time Data in Time-to-Event (or Survival) Analysis

This article is part of an extended series of tutorials for time-to-event (or survival) analysis. The next article is here. Introduction The following article is my attempt at applying the…
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