CSTAT Data Visualization Seminar Series (available for RCR Credit)

ATTENTION:

Graduate Students, Faculty

The Center for Statistical Training and Consulting is hosting the Data Visualization Seminar Series. Some of these events will count towards RCR credit for graduate students. View a full list of events hosted by CSTAT here: https://cstat.msu.edu/events.

Register for these events using the links below.

CSTAT Data visualization Seminar series

When communication research meets visual analytics: An integration of arts and sciences

  • May 9, noon - 1 p.m.

  • Dr. Winson Peng, Department of Communication, Michigan State University

Big data is “of the people, by the people, and for the people”. But data could not speak for itself.  The interdisciplinary collaboration between computer scientists and social scientists helps restore silent data into dynamic interaction between social topics. This talk will introduce two interdisciplinary studies (Xu et al., 2013; Sun et al., 2014) which aimed to examine how social issues compete and cooperate with one another for public attention on social media. Building upon classical agenda-setting theory in communication research, the two studies proposed two visual analytical systems that can facilitate panoramic and in-depth analysis of topic interaction on social media. Reflecting on this collaboration, I will discuss how social scientists and computer scientists can work together to create a 1+1>2 effect.

Initial data analysis in the example of Pokémon species

  • June 6, noon - 1 p.m.

  • Dr. Lara Lusa,  Natural  Sciences and Information Technologies, University of Primorska and Institute for Biostatistics and Medical Informatics, University of Ljubljana, Slovenia

(eligible for RCR credit for graduate students)

Initial Data Analysis (IDA) consists of all steps performed on the data of a study between the end of the data collection and start of statistical analyses that address research questions. The value of an effective IDA strategy for data analysts lies in ensuring that data are of sufficient quality, that model assumptions made in the analysis strategy are satisfied and are adequately documented, and in supporting decisions for the statistical analyses.  Here we focus on the data screening step of IDA, where data properties are examined and effective visualizations are a fundamental tool. The objective of our work is to present recommendations on how to implement an IDA plan, how to create visualizations that are effective for the IDA, and make use of the IDA findings.

To Find Out More, Press Play: Creating Accessible Statistics Videos

  • June 8, noon - 1 p.m.

  • Dr. Michael Wallace,  Department of Statistics and Actuarial Science, University of Waterloo, Canada

An important component of academic research is outreach: communicating ideas to those beyond our own specialisms. In this talk I will describe my experiences creating videos for the measurement error topic group of the STRengthening Analytical Thinking for Observational Studies (STRATOS) Initiative. The goal: take a complex statistical topic and produce introductory videos that are informative, accurate, but also accessible to a wide audience. I will discuss the process from conception to completion, highlighting important considerations ranging from content, copyright, to closed captions.

How do we make better graphs? Effective visual communication for the quantitative scientist

  • June 13, noon - 1 p.m.

  • Dr. Mark Baillie, Novartis, Switzerland

(eligible for RCR credit for graduate students)

Effective visual communication (EVC) is a core competency for all scientists who work with data, such as statisticians, pharmacometricians, epidemiologists, data scientists, etc. By using the right graphical principles, we can better understand data, highlight core insights, and influence decisions toward appropriate actions. Without them, we can mislead others and ourselves and pave the way to wrong conclusions and actions. The aim of this seminar is to provide an overview of EVC for quantitative scientists through a series of case studies and exercises, focusing on the key principles have a clear purpose, show the data clearly, and make the message obvious. Illustrative examples will be drawn from medical research, but the course is designed to be general for all quantitative experts communicating data, analyses, and conclusions. The seminar will help put the three EVC principles into practice.