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Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Statgraphics01:10

Statgraphics

Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
Methods of Documentation III: PIE01:21

Methods of Documentation III: PIE

Problem-intervention-evaluation (PIE) is a systematic approach to documentation used in healthcare settings for clinical decision-making and patient care planning. It is a structured approach to organizing patient data based on problems, interventions, and evaluations. Here's a breakdown of its key features and considerations:
Pie Chart01:04

Pie Chart

A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
Manipulation and Analysis01:21

Manipulation and Analysis

GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...

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Related Experiment Video

Updated: May 16, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

Developing Public-Friendly Visualisations to Improve PPIE Glossaries for Statistical Methodology Research.

Clareece R Nevill1, Hannah Cooper1, Barbara Czyznikowska2

  • 1Biostatistics Research Group, Division of Public Health and Epidemiology, School of Medical Sciences, University of Leicester, Leicester, UK.

Health Expectations : an International Journal of Public Participation in Health Care and Health Policy
|May 15, 2026
PubMed
Summary
This summary is machine-generated.

Visual aids were developed for 10 statistical terms to improve understanding for patients and the public in research. These new visualisations aim to enhance patient and public involvement and engagement in statistical methodology research.

Keywords:
Patient and Public Involvement and Engagement (PPIE)statistical methodologyvisualisations

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Area of Science:

  • Biostatistics and Statistical Methodology
  • Patient and Public Involvement and Engagement (PPIE)
  • Scientific Communication and Visualization

Background:

  • Plain-language definitions are crucial for public engagement in research.
  • Visual aids can significantly enhance understanding of complex technical terms.
  • Existing resources for PPIE in statistical methodology research are limited.

Purpose of the Study:

  • To develop visualisations for selected statistical methodology research terms.
  • To support Patient and Public Involvement and Engagement (PPIE) in statistical research.
  • To make complex statistical terminology more accessible and intuitive.

Main Methods:

  • Ten glossary definitions were selected for visualisation development.
  • Initial concepts were drafted by a working group and refined by a graphic designer.
  • Two cycles of public contributor feedback were incorporated to finalize designs.

Main Results:

  • Visualisations were created for terms including Bayesian, calibration, causal inference, censoring, deviance, discrimination, regression, Markov Chain Monte Carlo (MCMC), prognostic model, and simulation study.
  • Public feedback addressed language interpretation, layout simplicity, accessibility, and symbol clarity.
  • Insights from feedback were integrated to shape the final visual designs.

Conclusions:

  • Developed visualisations address the need for better PPIE resources in statistical methodology.
  • Ten visual aids were created to aid PPIE members in understanding complex statistical terms.
  • These visualisations are freely available online to support research engagement.