CSSCR Courses



To sign up for our free courses, scroll to the bottom of this page!

Spring 2017

Introduction to R with RStudio

Description:

This class will teach you how to get started with R using the free integrated development environment called RStudio. The course will cover the basic organization of R and Rstudio, where to find good help references, and how to begin a basic analysis. This class is ideal for users who have little or no experience with R.


Instructor: Gabby Gorsky, CSSCR Consultant
Date: Wednesday, 29 Mar 2017
Time: 10:30pm - 11:20pm Place: Savery 121
Register here.

Introduction to SPSS

Description:

This class introduces SPSS basic structure and layout. We will go over how to import, manage, and record data as well as do some descriptive statistics and simple analyses like t-test, correlation, and regression.


Instructor: Tina Tian, CSSCR Data Specialist
Date: Thursday 30 Mar 2017
Time: 9:30am - 10:20am Place: Savery 121
Register here.

Introduction to R with RStudio

Description:

This class will teach you how to get started with R using the free integrated development environment called Rstudio. The course will cover the basic organization of R and RStudio, where to find good help references, and how to begin a basic analysis. This class is ideal for users who have little or no experience with R.


Instructor: Yunkang Yang, CSSCR Consultant
Date: Friday, 31 Mar 2017
Time: 3:30pm - 4:20pm Place: Savery 121
Register here.

Basic Quantitative Analysis in Excel

Description:

This class will teach you how to do basic computation and quantitative analysis in Excel. The course introduces the programming and function call capabilities in Excel, and how to use them to perform basic data analysis.


Instructor: Baishakhi Basu, CSSCR Consultant
Date: Monday, 3 Apr 2017
Time: 2:00pm - 2:50pm Place: Savery 121
Register here.

Introduction to R with RStudio

Description:

This class will teach you how to get started with R using the free integrated development environment called RStudio. The course will cover the basic organization of R and Rstudio, where to find good help references, and how to begin a basic analysis. This class is ideal for users who have little or no experience with R.


Instructor: Nathan Abe, CSSCR Consultant
Date: Monday, 3 Apr 2017
Time: 3:30pm - 4:20pm Place: Savery 121
Register here.

Introduction to SAS

Description:

This introductory class will cover basic features and some data cleaning and recoding of variables in SAS. The topics include: an overview of the SAS system; how to read/enter data, modify, explore and manage data; and some basic data recoding and variable creation.


Instructor: Nikki Gurley, CSSCR Consultant
Date: Tuesday, 4 Apr, 2017
Time: 4:30pm - 5:20pm Place: Savery 121
Register here.

Introduction to R with RStudio

Description:

This class will teach you how to get started with R using the free integrated development environment called RStudio. The course will cover the basic organization of R and Rstudio, where to find good help references, and how to begin a basic analysis. This class is ideal for users who have little or no experience with R.


Instructor: Carolina Johnston, CSSCR Consultant
Date: Wednesday, 5 Apr 2017
Time: 9:00am - 9:50am Place: Savery 121
Register here.

Introduction to Stata

Description:

This class will teach you how to get started with Stata using do files. The course will cover the basic organization of Stata, where to find good help references, and how to begin a basic analysis and create a log file of results. This class is ideal for users who have little or no experience with Stata.


Instructor: Laine Rutledge, CSSCR Consultant
Date: Wednesday, 5 Apr 2017
Time: 10:00am - 10:50am
Place: Savery 121
Register here.

Data Wrangling in R

Description:

This course will cover some of R's useful tools for data management and exploration. Most of class will be devoted to learning Hadley Wickham's excellent tidyr and dplyr packages. Attendees will be assumed to have basic familiarity with R.


Instructor: Stephanie Lee, CSSCR Consultant
Date: Thursday, 6 Apr 2017
Time: 4:30pm - 5:20pm Place: Savery 121
Register here.

Introduction to R Base Graphics

Description:

This class will introduce students to ways of producing effective graphs in R. Topics covered will include basic plotting functions (histograms, scatter plots, etc.), production of multi-panel graphs, and various means for exporting graphs for use outside of R.


Instructor: Will Brown, CSSCR Consultant
Date: Friday, 7 Apr 2017
Time: 11:30am-12:20pm Place: Savery 121
Register here.

To register for the above classes, follow this link.

Other Seminars, Courses, etc.

Center for Studies in Demography and Ecology: Introduction to Graphics in R

Description:

This is an introduction to graphics in the statistical programming language.


Instructor:Cori Mar, CSDE Methods and Data Director
Date: Thursday, 6 Apr 2017
Time: 12:00pm-2:20pm Place: Savery 121
Register here (bottom of page).

Center for Studies in Demography and Ecology: Introduction to GIS

Description:

This workshop will begin by presenting an overview of the basic concepts of Spatial Analysis and Geographic Information Systems (GIS). Armed with an understanding of what GIS is, students will complete a hands-on tutorial introducing ESRI's ArcGIS software. Topics covered during the first week's lab will include: working with GIS data, simple data queries, and map creation (symbolization, labeling, layout and export). Building on the basic concepts covered during the first week, week 2 will focus entirely on hands-on training in GIS for demographic research. Topics covered in the second week's lab will include: acquiring GIS and census data, synthesizing multiple data sources, and basic GIS analysis.

This workshop meets twice, Monday April 10th and Monday April 17th from 1pm to 4pm. Signup once to be registered for both meetings.

Prerequisite: The workshop assumes no prior knowledge of GIS.


Instructor:Matt Dunbar, CSDE Research Scientist
Date: Monday, 10 Apr 2017
Time: 1:00pm-3:50pm Place: Savery 117
Register here (bottom of page).

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