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Workshops

Our drop-in workshops take place during Fall, Winter and Spring quarters. Check our site for currently scheduled workshops.  Stanford faculty and teaching/research staff can request an SSDS workshop by emailing us at: consult-ssds@lists.stanford.edu

Click here to view the Fall 2017 Workshop Schedule

 


Past Workshops

Intro to Python (Register at https://stanforduniversity.qualtrics.com/jfe/form/SV_8vNp8gS102a6zCl)

When: April 20, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

The objective of this workshop is to introduce students to the Python programming language and several libraries particularly useful for the humanities and social sciences. In learning basic Python syntax, we'll also learn to scrape information from the web and parse it for varied uses.

Preparation: Please consult this page to prepare your computer for the workshop: https://github.com/sul-cidr/python_workshops/blob/master/setup.ipynb  If you need help with the installation, please arrive 20 minutes early and we're happy to help you.
This workshop is offered by Stanford Libraries' Center for Interdisciplinary Research as part of its mission to provide training in technical academic research practices and applied research methods.

http://library.stanford.edu/events/introduction-python


Data Manipulation and Visualization with Python (Register at https://stanforduniversity.qualtrics.com/jfe/form/SV_8GOBGvOQf8Z9fFj)

When: April 27, 2017 (2-4 PM)

Where: East Asia Library, Room 338

Presenters: Javier de la Rosa & Scott Bailey

The objective of this workshop is to guide students through fundamentals of data manipulation and visualization with Pandas and Seaborn.  This workshop will assume some basic understanding of Python and programming; attendance at the Introduction to Python workshop is recommended.

Preparation: Please consult this page to prepare your computer for the workshop: https://github.com/sul-cidr/python_workshops/blob/master/setup.ipynb  If you need help with the installation, please arrive 20 minutes early and we're happy to help you.
This workshop is offered by Stanford Libraries' Center for Interdisciplinary Research as part of its mission to provide training in technical academic research practices and applied research methods.

http://library.stanford.edu/events/data-manipulation-and-visualization-p...


Natural Language Processing with Python (Register at https://stanforduniversity.qualtrics.com/jfe/form/SV_41PNzscrqFxcsPH)

When: May 11, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

The objective of this workshop is to teach students natural language processing in Python, with topics such as tokenization, part of speech tagging, and sentiment analysis.  This workshop will assume some basic understanding of Python and programming; attendance at the Introduction to Python workshop is recommended.

Preparation: Please consult this page to prepare your computer for the workshop: https://github.com/sul-cidr/python_workshops/blob/master/setup.ipynb  If you need help with the installation, please arrive 20 minutes early and we're happy to help you.
This workshop is offered by Stanford Libraries' Center for Interdisciplinary Research as part of its mission to provide training in technical academic research practices and applied research methods.

http://library.stanford.edu/events/natural-language-processing-python-0


Introduction to Machine Learning with Python (Register at https://stanforduniversity.qualtrics.com/jfe/form/SV_5cZOBjuhPAcbSqV)

When: May 25, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

The objective of this workshop is to introduce students to the principles and practice of machine learning using Python.  This workshop will assume some basic understanding of Python and programming; attendance at the Introduction to Python workshop is recommended.

Preparation: Please consult this page to prepare your computer for the workshop: https://github.com/sul-cidr/python_workshops/blob/master/setup.ipynb  If you need help with the installation, please arrive 20 minutes early and we're happy to help you.
This workshop is offered by Stanford Libraries' Center for Interdisciplinary Research as part of its mission to provide training in technical academic research practices and applied research methods.

http://library.stanford.edu/events/introduction-machine-learning-python


Using Jekyll and GitHub for Project Pages (Register at https://stanforduniversity.qualtrics.com/jfe/form/SV_3XiKqeHQbwhdFLn)

When: June 1, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

The objective of this workshop is to teach students how to use Jekyll and GitHub to set up and deploy webpages.

This workshop is offered by Stanford Libraries' Center for Interdisciplinary Research as part of its mission to provide training in technical academic research practices and applied research methods.

http://library.stanford.edu/events/using-jekyll-and-github-project-pages


Natural Language Processing with Python (Register at https://stanforduniversity.qualtrics.com/SE/?SID=SV_bm9w6tyyhSM6Gvb)

When: March 9, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

This workshop will teach students natural language processing in Python, with topics such as tokenization, part of speech tagging, and sentiment analysis.

https://events.stanford.edu/events/657/65723/


Data Manipulation with Python (Register at https://stanforduniversity.qualtrics.com/SE/?SID=SV_0CmVJv4nFhlaGtT )

When: February 16, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

This workshop will guide students through fundamentals of data manipulation and visualization with Pandas and Seaborn.

https://events.stanford.edu/events/657/65721/

Intro to Python (Register at https://stanforduniversity.qualtrics.com/SE/?SID=SV_1NORdcNlo9QQb5z)

When: January 26, 2017 (2-4 PM)

Where: Green Library 121A

Presenters: Javier de la Rosa & Scott Bailey

The objective of this workshop is to introduce students to the Python programming language and several libraries particularly useful for the humanities and social sciences. In learning basic Python syntax, we'll also learn to scrape information from the web and parse it for varied uses.

Preparation: Please install Anaconda with Python 3.5. If you need help with the installation, please arrive 20 minutes early and we're happy to help you.

https://events.stanford.edu/events/657/65719/


Text Analytics for Social Data Using DiscoverText & Sifter

When: Tuesday, January 17, 2017 (Three Repeating Sessions)

Where:  Session A: 10-11:30 AM – Green Library Bing Wing, Room 121A

                Session B: 1:30-2:50 PM – McClatchy Hall

                Session C: 3:15-4:45 PM – Green Library Bing Wing, Room 121A

Presenter: Dr. Stuart W. Shulman

Please RSVP to reserve a seat:http://web.stanford.edu/group/iriss/iriss-forms/discovertext.fb

Participate in this workshop to learn how to build custom machine classifiers for sifting social media data. The topics covered include how to:

  • construct precise social data fetch queries,
  • use Boolean search on resulting archives,
  • filter on metadata or other project attributes,
  • count and set aside duplicates, cluster near-duplicates,
  • crowd source human coding,
  • measure inter-rater reliability,
  • adjudicate coder disagreements, and
  • build high quality word sense and topic disambiguation engines.

DiscoverText collects and cleans up messy Twitter and other text data streams. The workshop covers how to reach and substantiate inferences using a theoretical and applied model informed by a decade of interdisciplinary, NSF-funded research into the text classification problem. Participants will learn how to apply “CoderRank” in machine learning.  The major idea of the workshop is that when training machines for text analysis, researchers should rely on the input of those humans most likely to create a valid observation. 

Bio

Dr. Stuart W. Shulman is founder & CEO of Texifter.  He was a Research Associate Professor of Political Science at the University of Massachusetts Amherst and the founding Director of the Qualitative Data Analysis Program (QDAP) at the University of Pittsburgh and at UMass Amherst. Dr. Shulman is Editor Emeritus of the Journal of Information Technology & Politics, the official journal of Information Technology & Politics section of the American Political Science Association.

More information about Discovertext and Sifter

https://iriss.stanford.edu/events/discovertext-info-session

This workshop is hosted by IRiSS (Institute for Research in the Social Sciences) and

SSDS (Social Science Data and Software)


Introduction to R

When: Wednesday, November 2, 2016 (2-4 PM)

Where: The SSRC Classrom, 121A, First Floor, Green Library Bing Wing

The objective of this workshop is to introduce students to the R programing language and some basic functions useful for statistical analysis, data manipulation and visualization.
 
Come prepared: Please, download R and R Studio in your laptop ahead of time. Here is a short video to guide you through the installation process (for PC and for Mac). If you need some assistance installing these programs please arrive on Wednesday 20 minutes before the begining of the workshop. I’ll be there to help you!
 
NOTE for Mac Users: Some functions in R require an “X11 Server” and/or libraries associated with an X11 server. You need to download XQuartz. (Here is some useful info)

Here are links for the slides, tutorials, and solutions for the exercises from the workshop:


Using Dedoose for Qualitative or Mixed-Methods Research

When: Wednesday, May 25, 2016 (Noon-1pm)

Where: The Velma Denning room (120F), First floor, Green Library Bing Wing

RSVP: consult-ssds@lists.stanford.edu

Learn how to use Dedosse, a Web-based application that works with Windows or Mac, to to analyze your qualitative or mixed-methods research with text, photos, audio or video, and spreadsheet data.

Topics: Creating a project; Uploading Media; Creating and applying codes; Using descriptors; Visualizing patterns; Collaborative projects; Mixed-method projects


R Basics Open Lab

When: Thursday, May 26, 2016 (5-6:30pm)

Where: The Velma Denning Room (120F), first floor, Green Library Bing Wing

This free short course will introduce students to the R pprogramming language and some basic functions useful for statistical analysis, data manipulation and visualization.  This open lab provides an interactive tutorial where students will work at their own pace.  Instructors will answer questions about the provided scripts and beyond.  We also welcome advanced R. students.

Topics: Setting up the R workspace; Creating and storing objects; Functions; R packages, Reading data; Selecting and sub-sampling data; Merging and appending datasets.

Come prepared: You are welcome to use the cluster computers in the Velma Denning Room for this tutorial (you will need a SUNet ID).  If you plan to use your own laptop, please download and install R and R Studio ahead of time.

Should you need help installing these programs, please contact us


Using Stata for Data Analysis: May 4, May 11, & May 18, 2016

Time:  Noon-1:30p - Where: Room 121A (SSRC Seminar Room), Green Library, Bing Wing

Please bring your laptops to follow along. 

Download materials for participants. RSVP: consult-ssds@lists.stanford.edu

(Don't have Stata. Read our Getting Started Guides  on an "Introduction to Farmshare for Statistical Packages" under Accessing and Using Software in Farmshare)


Wednesday, May 4, 2016

Introduction to StataGraphical user interface; Importing & exporting data: Understanding your data (e.g., describe, list, summarize, tabulate); Using do-files & log-files; Using help files; Organizing Stata files and folders

Data Cleaning Renaming variables; labeling variables & values; Identifying duplicate observations; Dropping observations & variables; Editing variables (recode, replace, & generate; destring & tostring); Re-ordering variables


Wednesday, May 11, 2016

Data Management Appending; Merging; Reshaping; Collapsing

Correlation & T-test Correlation: Using the correlate command; Using the pwcorr command T-test: One-sample; Paired; Two independent samples

Other Statistical Tests One-way ANOVA; Chi-square; Factor analysis


Wednesday, May 18, 2016

Regression Analysis & Graphing: Regression analysis: Ordinary least squares regression; Binary logistic regression

Graphing: Histograms; Scatterplots; Bar graphs

Advanced Topics: Globals & locals; Loops; Weights; Using egen; Using estout


Introduction to R
 
When: Monday, April 11, 2016 (11:30-1:00)
Where: Green Library East: Information Center Classroom (166).
Topics Covered
  • Objects
  • Functions
  • R Packages
  • Reading Data
  • Transforming Data
  • Analyzing Data
  • Intro to Graphs
Please come prepared to follow along with your laptop.  Download these links prior to the session: