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This is an archive of our past training offerings. We are looking to include workshops on topics not yet covered here. Is there something not currently on the list? Send us a proposal.

E.g., 22-Apr-18
E.g., 22-Apr-18
February 12, 2018
Coordinator:
Evan Muzzall

R FUN!damentals Part 3: Data Exploration and Analysis

Students will be introduced to data exploration and analysis in R. You will learn how to summarize data and explore it with histograms, scatterplots, and boxplots. You will also be introduced to coding statistical data analysis via t-tests, analyses of variance, correlation, and linear regression.

February 9, 2018
Coordinator:
Patty Frontiera

Geospatial data are an important component of social science and humanities data visualization and analysis. The R programming language is a great platform for exploring these data and integrating them into your research. 

Geospatial Data in R, part I: Getting started with spatial data objects

February 7, 2018
Coordinator:
Evan Muzzall

R FUN!damentals Part 2: Subsetting and Reshaping

February 7, 2018
Coordinator:
Soumya Gupta

This four-part, interactive workshop series is your complete introduction to programming Python for people with little or no previous programming experience. By the end of the series, you will be able to apply your knowledge of basic principles of programming and data manipulation to a real-world social science application.

Part 1 Topics:

February 6, 2018
Coordinator:
Janet Torres

In this workshop we will be using QGIS to visualize census data. We will cover some of the principles of visualizing geographic data, how to calculate rates in QGIS and how to aggregate data. 

Technology Requirement: Bring a laptop with QGIS installed.

February 5, 2018
Coordinator:
Evan Muzzall

Data are the foundations of the social and biological sciences. Familiarizing yourself with a programming language can help you better understand the roles that data play in your field. Learn to develop and train your data skills at the free D-Lab R workshops!

February 5, 2018
Coordinator:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction

February 1, 2018
Coordinator:
Josué Meléndez Rodríguez

This workshop offers a very basic introduction to qualitative research. First, an overview of the qualitative research process will be presented. Then, attendees will briefly explore (a) philosophical considerations regarding research, (b) qualitative methodologies and methods, and (c) ways in which technology can aid the qualitative research process.

February 1, 2018
Coordinator:
Kimberly Rubens

This class will cover the basics of Excel, from simple formulas (SUM, COUNTIF) to more complex Excel features like Macros and the Data Analysis ToolPak. By the end of both sections, students will be able to employ Excel skills to open source policy data sets. These skills are transferrable to any sector.

Topics Covered Will Include:

January 30, 2018
Coordinator:
Kimberly Rubens

This class will cover the basics of Excel, from simple formulas (SUM, COUNTIF) to more complex Excel features like Macros and the Data Analysis ToolPak. By the end of both sections, students will be able to employ Excel skills to open source policy data sets. These skills are transferrable to any sector.

Topics Covered Will Include:

January 30, 2018
Coordinator:
Janet Torres

This workshop will introduce participants to geospatial data concepts, formats and tools. We will provide an overview of the different types of geospatial data and how to find freely available open source data online. We will load and explore sample data set in QGIS, a widely used free and open source GIS software application.

January 29, 2018
Coordinator:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction

January 24, 2018
Coordinator:
Susan Powell

This workshop will introduce participants to geospatial data concepts, formats and tools. We will provide an overview of the different types of geospatial data and how to find freely available open source data online. We will load and explore sample data set in QGIS, a widely used free and open source GIS software application.

January 22, 2018
Coordinator:
Jackie Ferguson

This three-part series will cover the following materials:

Part 1:  Introduction

January 18, 2018
Coordinator:
Lindsay Bayham

This interactive workshop will discuss how to analyze qualitative data, including how to develop codes, look for patterns, answer research questions, and build an argument in order to write the findings, discussion, and conclusion sections of a research paper. Researchers at any stage in the process are welcome.

January 18, 2018
Coordinator:
Lindsay Bayham

This workshop focuses on how to organize and code qualitative data in Dedoose. The training will outline key decisions researchers must make in the coding process, as well as review how to start a new project and engage in basic tasks.

January 17, 2018
Coordinator:
Zawadi Rucks-Ahidiana

This workshop focuses on how to organize and code qualitative data in MaxQDA. The training will outline key decisions researchers must make in the coding process, as well as review how to start a new project and engage in basic tasks.

January 16, 2018
Coordinator:
Josué Meléndez Rodríguez

This workshop will introduce participants to the use of qualitative data analysis (QDA) software and provide an overview of popular programs. This workshop is ideal for researchers who are new to the idea of using QDA software.

January 16, 2018
Coordinator:
Josué Meléndez Rodríguez

This workshop offers a very basic introduction to qualitative research. First, an overview of the qualitative research process will be presented. Then, attendees will briefly explore (a) philosophical considerations regarding research, (b) qualitative methodologies and methods, and (c) ways in which technology can aid the qualitative research process. 

 

January 12, 2018
Coordinator:
Evan Muzzall

R FUN!damentals Part 4: For-loops and Functions

Students will learn how to write for-loops and functions in R. You will learn how to personalize functions via control structures such as ‘if’ and ‘else’. These learning objectives will be exemplified through introduction to the construction and graphical representation of Monte Carlo resampling simulation.

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