| Introduction to HPC |
February 3rd
Main Lab
10am-12pm |
Got big data? Andrew Sherman, HPC Specialist, will present the world of High Performance Computing at Yale. You will find out what HPC means, which services are available and how to access them. |
| Introduction to LaTeX |
February 3rd
Rosenkranz Lab
2-4pm |
One of our most popular workshops. Statistical experience *not* required. LaTeX is the document preparation system most commonly used for scientific and quantitative publishing. See the LaTeX Project Page for more information. This workshop will provide an introduction to different LaTeX environments and workflows. We will discuss several standards for publishing, presentation and document management. |
Introduction to R
|
February 10th
Main Lab
10am-12pm |
R is a free, open source programming language for statistical computing and graphics. R has a large and constantly growing list of add-ons including GIS, graphing, advanced statistics, econometrics, image analysis and more. This class offers an basic introduction to programming in R and resources available. Basic statistical understanding is expected. If there is one application you will want to know other than your current app of expertise (Stata, Matlab, SPSS) it would be R. |
Introduction to SPSS
|
February 10th
Rosenkranz Lab
2-4pm |
SPSS is a flexible and user-friendly statistical software package known for its graphics and ease of use. SPSS also works directly with Excel files. This class offers an introduction to the application, opening and manipulating files and running basic analyses. Basic statistical understanding is expected but not necessary. |
| Introduction to Stata |
February 17th
Main Lab
10am-12pm |
Stata is a popular statistical program used by academic researchers across campus, especially in economics, political science, and EPH. If you are a total to moderate rookie with Stata (i.e. have never used or only ever used "regress" for class) and want to learn more about importing, merging, and cleaning your data, this class is for you. We will cover the basics: getting around the program, do files, graphics and table generation. |
Writing Papers with Data
|
February 17th
Rosenkranz Lab
2-4pm |
This workshop is designed for undergraduates writing a paper using data and analysis for the first time. We’ll cover translating your research idea into a quantifiable question and finding the right data to answer that question. Topics will include: statistical significance, sample size, independent vs dependent variables, and correlation vs. causation. No statistical experience required. |
Introduction to Survey Design
|
February 24th
Main Lab
10am-12pm |
Surveys are an easy way to capture important data. This workshop helps determine what data to gather and how to gather that information. Topics will include: determining your audience, basic survey design, the characteristics of good and bad questions, and some basic statistical concepts to keep in mind when designing a survey. Basic statistical understanding is not expected. |
Intermediate R
|
February 24th
Rosenkranz Lab
2-4pm |
This class assumes basic knowledge of R and statistics. Topics include the various data types in R, reading in data, graphing, matrix manipulations and using and writing your own statistical functions. |
Overview of Qualtrics
PowerPoint Slides |
March 2nd (CSSSI 2-4pm) |
Qualtrics is an easy to use but very sophisticated online survey tool that is now
available to students, staff and faculty at Yale. This workshop will introduce you to some of the features
of the software and allow you to begin designing your own questionnaires and using the online data tools. |
Spring Break March 2nd-18th
|
| Introduction to Qualitative Data Analysis |
March 23rd
Main Lab
10am-12pm |
This workshop will discuss the process of quantifying qualitative data such as transcripts and other text as well as multimedia. We will demonstrate Linguistic Inquiry and Word Count (LIWC) and Nvivo, two software packages that can help gather and organize your data. |
| Advanced Excel for Data Analysis |
March 23rd
Rosenkranz Lab
2-4pm |
This class assumes basic knowledge of Microsoft Excel. Topics include importing and exporting, working with data sets, pivot tables/charts, advanced graphic, using built-in functions and writing your own statistical functions. |
| Intermediate/Advanced GIS |
March 30th
Main Lab
9:30am-Noon |
This session will build upon the skills and concepts introduced in the "Introduction to Geographic Information Systems and ArcGIS for Spatial Analysis" session and participants will be expected to attend that workshop, or have comparable experience with ArcGIS 10. Topics will include: Creation of Geodatabases; Use of Relates & Relationship Classes; Geoprocessing of geographic data; Georeferencing; Geocoding of street addresses; Use and Creation of Raster Data; Overlay Analysis; and Advanced Manipulation of Tabular Data.
|
Introduction to Basic GIS for Research
|
March 30th
Rosenkranz
MOVED
TO CSSSI
2-4pm |
This is an introduction to the basic concepts of creating, managing and analyzing data within a Geographic Information Systems (GIS) framework. This workshop is taught by one of our Political Science grad students who has been working heavily in GIS for the last year. This introduction points out many of the pitfalls common to beginning users of ArcGIS while emphasizing solutions for commonly repeated tasks. |
| Introduction to SAS |
April 13th
Main Lab
10am-12pm |
SAS is an extremely powerful statistical package that can be very useful - when not overwhelming. SAS is the gold standard in publishing for clinical, medical and marketing data analysis. SAS is also available for free for Yale students. This class offers a basic introduction to the application, writing code, loading and manipulating data, and running simple statistics. Basic statistical understanding is expected. |
Intermediate Stata
|
April 13th
Rosenkranz Lab
2-4pm |
This Stata workshop covers more than the basics. Topics will include some (but not all) of the following: different regression models, working with StatTransfer, OutReg, flow control, working with .do and .ado files, graphics, merging/splitting datasets, graphing and working with large sets of data. |
