Data Science Training at MSU

Data science training is offered through a partnership between Social Data Collection and Analysis Services and the Library.

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Workshop recordings and materials

MSU R workshops team

Workshop Recordings and Materials

All workshop materials are available under a Creative Commons Attribution license. If you have questions or need additional help related to workshop topics, MSU provides the following resources:

The Math and Stat Center provides help for select courses. Check to see if your course is listed on their page.
Statistical Resources may be able to refer you to additional help.

Intro to R Data Visualization Intermediate R Data Wrangling Intro to Python

Introduction to R

Recording date: Fall 2024
Instructors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher
Contributors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher, Harley Clifton, Elliot Liucci, Mark Greenwood, Allison Theobold, The Carpentries
Publisher: Montana State University

Prior to the workshop, please make sure you have recent versions of R and RStudio on your computer. This guide can help you: https://rstudio-education.github.io/hopr/starting.html

Download workshop materials

Data Visualization in R

Recording date: Fall 2024
Instructors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher
Contributors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher, Harley Clifton, Elliot Liucci, Mark Greenwood, Allison Theobold, The Carpentries
Publisher: Montana State University
Online tutorial is available here: https://rconnect.math.montana.edu/Data_viz_tutorial/

Intermediate R

Recording date: Fall 2022
Instructors: Greta Linse, Sara Mannheimer, Harley Clifton, Elliot Liucci
Contributors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher, Harley Clifton, Elliot Liucci, Mark Greenwood, Allison Theobold, The Carpentries
Publisher: Montana State University
Online tutorial is available here: https://rconnect.math.montana.edu/IntermediateR/

Data Wrangling in R

Recording date: Fall 2024
Instructors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher
Contributors: Greta Linse, Sara Mannheimer, Ava Yasdian, Sally Slipher, Harley Clifton, Elliot Liucci, Mark Greenwood, Allison Theobold, The Carpentries
Publisher: Montana State University
Online tutorial is available here: https://rconnect.math.montana.edu/Data_Wrangling/

Introduction to Python

Prior to the workshop:

Download and install Anaconda Navigator (https://www.anaconda.com/anaconda-navigator).
Download this ZIP file.
Unzip the file and save the contents locally on your computer.
Open Anaconda Navigator and launch “Jupyter Lab”.
Open the “IntroPython.ipynb” file from the zipped folder.

Download workshop materials

Montana State University R Workshops Team

These materials were adapted from materials generated by the Data Carpentries (https://datacarpentry.org/) and were originally developed at MSU by Dr. Allison Theobold. The workshop series is co-organized by the Montana State University Library, Department of Mathematical Sciences, and Statistical Consulting and Research Services (SCRS, https://www.montana.edu/statisticalconsulting/). SCRS is supported by Montana INBRE (National Institutes of Health, Institute of General Medical Sciences Grant Number P20GM103474). The workshops for 2020-2021 are supported by Faculty Excellence Grants from MSU’s Center for Faculty Excellence.

Research related to the development of these workshops is to appear in:

Theobold, A., Hancock, S., & Mannheimer, S.. Data Science Workshops for Data-Intensive Environmental Science Research, Journal of Statistics Education 29 (sup1), S83-S94. https://doi.org/10.1080/10691898.2020.1854636

These workshops involve modifications of materials.

$Creative Commons License$ This work is licensed under a Creative Commons Attribution 4.0 International License

Current Workshop Instrutors

Sara Mannheimer

Sara Mannheimer is an Associate Professor and Data Librarian at Montana State University, where she helps shape practices and theories for curation, publication, and preservation of data. Her research examines the social, ethical, and technical issues of a data-driven world. She is the project lead for the MSU Dataset Search and the Responsible AI project.

Greta Linse

Greta Linse is the Interim Director of Statistical Consulting and Research Services and the Project Manager for the Human Ecology Learning and Problem Solving (HELPS) Lab. Greta has been teaching, documenting and working with statistical software including R and RStudio for over 10 years.

Sally Slipher

Sally Slipher is a research statistician for Social Data. She has taught statistics in the past and uses R extensively (and sometimes other coding languages) to explore data and put together analyses.

Ava Yazdian

Ava Yazdian is a current sophomore studying conservation biology and ecology. She enjoys helping others learn the language of statistics and data analysis through her experience in her statistics coursework. Her interests include plant ecology, skiing, and ceramics.

Previous Contributors

Harley Clifton

Harley Clifton is an undergraduate senior pursuing a degree in Mathematics (Statistics Option) with a minor in Psychology. She enjoys teaching nuanced coding skills and Data Visualization strategies through her experience as a Teaching Assistant for STAT 216 and STAT 408. Harley recently attended the Summer Institute in Biostatistics and Undergraduate Data Science at the University of California Irvine, funded by the National Institute Of Allergy And Infectious Diseases of the National Institutes of Health (under Award Number R25AI170491). Her areas of interest include quantifying behaviors and societal attitudes, behavior modification to reduce discrimination, Deaf culture and history, and women’s health.

Eliot Liucci

Eliot Liucci is a senior in the Mathematics (Statistics Option) Program here at Montana State University. He is currently working on a research project with the Mathematics and Statistics Center to analyze the impact of different time based variables on overall MSC foot traffic and usage. Throughout his experience as a Teaching Assistant for STAT 216 and STAT 217, Eliot has gained a deeper understanding of statistical methods and educational approaches. Eliot will graduate at the end of Fall 2022 with his bachelors and will start the M.S. in Statistics program in Spring 2023. His interests include environmental statistics, video games, and he restores vintage automobiles and motorcycles in his free time.

Mark Greenwood

Mark Greenwood is a Professor of Statistics in the Department of Mathematical Sciences at Montana State University and the former Director of Statistical Consulting and Research Services. His research interests have involved statistical methods and applications in environmental sciences, education, and biological sciences. Recent work has involved researching diagnostic methods for Multiple Sclerosis. His current research grants include funding from the Mountain West IDeA Clinical and Translational Research - Infrastructure Network (National Institute of General Medical Sciences Grant 5U54GM104944-08) and a grant from the National Multiple Sclerosis Society (RG-1907-34348).