Statistical Software and Data Workshops, Fall 2017
New Brunswick Libraries Data Workshop Series
Fall 2017
This Fall, Ryan Womack, Data Librarian, will offer a series of workshops on statistical software, data visualization, and reproducible research as part of New Brunswick Libraries Data Management Services. A detailed calendar and descriptions of each workshop are below. This semester each workshop topic will be repeated twice, once at the Library of Science and Medicine on Busch Campus, and once at Alexander Library on College Ave. These sessions will be identical except for location. Sessions will run approximately 3 hours. Workshops in parts will divide the time in thirds. For example, the first SPSS, Stata, and SAS workshop (running from 123 pm) would start with SPSS at 12 pm, Stata at 1 pm, and SAS at 2 pm. You are free to come only to those segments that interest you. There is no need to register, just come!
Logistics
Location: The Library of Science and Medicine (LSM on Busch) workshops will be held in the Conference Room on the 1st floor of LSM on Wednesdays from 12 to 3 pm. The Alexander Library (College Ave) workshops will be held in room 413 of the Scholarly Communication Center (4th floor of Alexander Library) from on Tuesdays from 1:10 to 4:10 pm.
For both locations, you are encouraged to bring your own laptop to work in your native environment. Alternatively, at Alexander Library, you can use a library desktop computer instead of your own laptop. At LSM, we will have laptops available to borrow for the session if you don’t bring your own. Room capacity is 25 in both locations, first come, first served.
If you can’t make the workshops, or would like a preview or refresher, screencast versions of many of the presentations are already available at http://libguides.rutgers.edu/data and https://youtube.com/librarianwomack. Additional screencasts are continually being added to this series. Note that the “special topics” [Time Series, Survival Analysis, and Big Data] are no longer offered in person, but are available via screencast.
Calendar of workshops
Tuesday (Alexander)
1:10 pm 4:10 pm 
Wednesday (LSM)
12 noon – 3 pm 

September 12  Introduction to SPSS, Stata, and SAS  September 13 
September 19  Introduction to R  September 20 
September 26  Data Visualization in R  September 27 
October 3  Reproducible Research  October 18 
Description of Workshops:
§ Introduction to SPSS, Stata, and SAS (September 12 or September 13) provides overviews of these three popular commercial statistical software programs, covering the basics of navigation, loading data, graphics, and elementary descriptive statistics and regression using a sample dataset. If you are already using these packages with some degree of success, you may find these sessions too basic for you.
 SPSS is widely used statistical software with strengths in survey analysis and other social science disciplines. Copies of the workshop materials, a screencast, and additional SPSS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208425. SPSS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SPSS is also available in campus computer labs and via the Apps server (see below).
 Stata is flexible and allows relatively easy access to programming features. It is popular in economics among other areas. Copies of the workshop materials, a screencast, and additional Stata resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208427. Stata is made available by OIRT via campus license with no additional charge to install for Rutgers users. Find it at software.rutgers.edu.
 SAS is a powerful and longstanding system that handles large data sets well, and is popular in the pharmaceutical industry and health sciences, among other applications. Copies of the workshop materials, a screencast, and additional SAS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208423. SAS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SAS is also available in campus computer labs, online via the SAS University Edition cloud service, and via the Apps server (see below).
Note: Accessing software via apps.rutgers.edu
SPSS, SAS, Stata, and R are available for remote access on apps.rutgers.edu. apps.rutgers.edu does not require any software installation, but you must activate the service first at netid.rutgers.edu.
§ Introduction to R (September 19 or September 20) – This session provides a threepart orientation to the R programming environment. R is freely available, open source statistical software that has been widely adopted in the research community. Due to its open nature, thousands of additional packages have been created by contributors to implement the latest statistical techniques, making R a very powerful tool. No prior knowledge is assumed. The three parts cover:
 Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
 Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
 Data Manipulation: data import and transformation, additional methods for working with large data sets, also dplyr and other packages from the tidyverse useful for manipulation.
Additional R resources, including handouts, scripts, and screencast versions of the workshops, can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Data Visualization in R (September 26 or September 27) discusses principles for effective data visualization, and demonstrates techniques for implementing these using R. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background. The three parts are:
 Principles & Use in lattice and ggplot2: discusses classic principles of data visualization (Tufte, Cleveland) and illustrates them with the use of the lattice and ggplot2 packages. Some of the material here overlaps with Intro to R, pt 2, but at a higher level.
 Miscellany of Methods: illustrates a wide range of specific graphics for different contexts
 3D, Interactive, and Big Data: presentation of 3D data, interactive exploration data, and techniques for large datasets. Relevant packages such as shiny and tessera are explored.
Additional R resources can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Reproducible Research (October 3 or October 18) covers
 Reproducible research describes the growing movement to make the products of research accessible and usable by others in order to verify, replicate, and extend research findings. This session reviews how to plan research, to create publications, code, and data in open, reusable formats, and maximize the impact of shared research findings. Examples in LaTeX and Rmarkdown are discussed, along with platforms for reusability such as the Open Science Foundation.
Additional resources on reproducible research and data management, including presentation slides, can be found here: http://libguides.rutgers.edu/datamanagement
§ Special Topics
Note that the following special topics are no longer covered by inperson workshops, but are available via screencast.
 Time Series in R: review of commands and techniques for basic time series analysis in R. Screencast at https://www.youtube.com/playlist?list=PLCj1LhGni3hOA2q0sfDNKBH9WIlLxXkbn and scripts at http://libguides.rutgers.edu/data_R
 Survival Analysis in R: review of commands and techniques for basic survival analysis in R. Scripts at http://libguides.rutgers.edu/data_R. Screencast at https://www.youtube.com/playlist?list=PLCj1LhGni3hOON9isnuVYIL8dNwkvwqr9.
 Big Data in Brief: an introduction to some of the techniques and software environments used to work with big data, with pointers to resources for further learning at http://libguides.rutgers.edu/bigdata. Screencast at https://www.youtube.com/playlist?list=PLCj1LhGni3hMNhIdrvz1F5JHIWi1qdX1
Mongolia GIS
While researching my upcoming Mongolia trip, I was amazed to discover a treasure trove of Mongolian data already at Rutgers. Christopher Free, a quantitative ecologist, studies Mongolian fisheries, and is an R and GIS expert to boot. He has compiled a onestop archive for Mongolian GIS data and R courses that use Mongolian fish data as examples [much better than sports statistics!].
These are exactly the kinds of global connections I am delighted to make!
Survival Analysis in R video available
As promised earlier, the “special topic” material on Survival Analysis is now available on YouTube in lieu of inperson sessions. Take a look at the Survival Analysis in R Playlist.
Survival analysis deals with data that may have truncated observations, called censored data. A typical example is studying the time until failure of a part in engineering, or failure of a part of the human body in medicine (colloquially known as “disease”). We usually have some accurate data on when the problem occurs until the point that the end of the study is reached. Then we will have some subjects that survived without failure until the end of the study, but we are uncertain just how long they would have lasted until failure. The methods of survival analysis account for this partial uncertainty in the data. R can deal with almost all necessary aspects of survival analysis, but requires some mixing and matching of packages to get the best results, as shown in the videos.
As always, my YouTube videos are fueled by music behind the scenes. Giving a throwback shoutout to Public Image Limited, some holiday Twice, plus the usual Mongolian suspects.
Statistical Software and Data Workshops, Fall 2016
Rutgers University Libraries Data Services Workshop Series (New Brunswick)
Fall 2016
This Fall, Ryan Womack, Data Librarian, will offer a series of workshops on statistical software, data visualization, and data management, as part of the Rutgers University Libraries Data Services. A detailed calendar and descriptions of each workshop are below. This semester each workshop topic will be repeated twice, once at the Library of Science and Medicine on Busch Campus, and once at Alexander Library on College Ave. These sessions will be identical except for location. Sessions will run approximately 3 hours. Workshops in parts will divide the time in thirds. For example, the first SPSS, Stata, and SAS workshop (running from 123 pm) would start with SPSS at 12 pm, Stata at 1 pm, and SAS at 2 pm. You are free to come only to those segments that interest you. There is no need to register, just come!
Logistics
Location: The Library of Science and Medicine (LSM on Busch) workshops will be held in the Conference Room on the 1st floor of LSM on Wednesdays from 12 to 3 pm. The Alexander Library (College Ave) workshops will be held in room 413 of the Scholarly Communication Center (4th floor of Alexander Library) from on Thursdays from 1:10 to 4:10 pm.
For both locations, you are encouraged to bring your own laptop to work in your native environment. Alternatively, at Alexander Library, you can use a library desktop computer instead of your own laptop. At LSM, we will have laptops available to borrow for the session if you don’t bring your own. Room capacity is 25 in both locations, first come, first served.
If you can’t make the workshops, or would like a preview or refresher, screencast versions of many of the presentations are already available at http://libguides.rutgers.edu/data and https://youtube.com/librarianwomack. Additional screencasts are continually being added to this series. Note that the “special topics” [Time Series, Survival Analysis, and Big Data] are no longer offered in person, but are available via screencast.
Calendar of workshops
Wednesday (LSM)
12 noon – 3 pm 
Thursday (Alexander)
1:10 pm 4:10 pm 

September 21  Introduction to SPSS, Stata, and SAS  September 22 
September 28  Introduction to R  September 29 
October 5  Data Visualization in R  October 6 
October 19  Introduction to Data Management  October 13 
Description of Workshops:
§ Introduction to SPSS, Stata, and SAS (September 21 or September 22) provides overviews of these three popular commercial statistical software programs, covering the basics of navigation, loading data, graphics, and elementary descriptive statistics and regression using a sample dataset. If you are already using these packages with some degree of success, you may find these sessions too basic for you.
 SPSS is widely used statistical software with strengths in survey analysis and other social science disciplines. Copies of the workshop materials, a screencast, and additional SPSS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208425. SPSS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SPSS is also available in campus computer labs and via the Apps server (see below).
 Stata is flexible and allows relatively easy access to programming features. It is popular in economics among other areas. Copies of the workshop materials, a screencast, and additional Stata resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208427. Stata is made available by OIRT via campus license with no additional charge to install for Rutgers users. Find it at software.rutgers.edu.
 SAS is a powerful and longstanding system that handles large data sets well, and is popular in the pharmaceutical industry, among other applications. Copies of the workshop materials, a screencast, and additional SAS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208423. SAS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SAS is also available in campus computer labs, online via the SAS University Edition cloud service, and via the Apps server (see below).
Note: Accessing software via apps.rutgers.edu
SPSS, SAS, Stata, and R are available for remote access on apps.rutgers.edu. apps.rutgers.edu does not require any software installation, but you must activate the service first at netid.rutgers.edu.
§ Introduction to R (September 28 or September 29) – This session provides a threepart orientation to the R programming environment. R is freely available, open source statistical software that has been widely adopted in the research community. Due to its open nature, thousands of additional packages have been created by contributors to implement the latest statistical techniques, making R a very powerful tool. No prior knowledge is assumed. The three parts cover:
 Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
 Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
 Data Manipulation: data import and transformation, additional methods for working with large data sets, also plyr and other packages useful for manipulation.
Additional R resources, including handouts, scripts, and screencast versions of the workshops, can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Data Visualization in R (October 5 or October 6) discusses principles for effective data visualization, and demonstrates techniques for implementing these using R. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background. The three parts are:
 Principles & Use in lattice and ggplot2: discusses classic principles of data visualization (Tufte, Cleveland) and illustrates them with the use of the lattice and ggplot2 packages. Some of the material here overlaps with Intro to R, pt 2, but at a higher level.
 Miscellany of Methods: illustrates a wide range of specific graphics for different contexts
 3D, Interactive, and Big Data: presentation of 3D data, interactive exploration data, and techniques for large datasets. Relevant packages such as shiny and tessera are explored.
Additional R resources can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Introduction to Data Management (October 13 or October 19) covers
 Best Practices for Managing Your Data – methods to organize, describe, backup, and archive your research data in order to ensure its future usability and accessibility. Developing good habits for handling your data from the start will save time and frustration later, and increase the ultimate impact of your research.
 Data Management Plans, Data Sharing and Archiving – targeted to researchers who need to write data management plans (DMPs) and share their data as part of their grant application, research and publication process. Reviews DMP guidelines, checklist, and general advice, along with options for sharing and permanently archiving research data.
 Reproducible Research – covers the growing movement to make the products of research accessible and usable by others in order to verify, replicate, and extend research findings. Reviews how to plan research, to create publications, code, and data in open, reusable formats, and maximize the impact of shared research findings.
Additional data management resources, including presentation slides, can be found here: http://libguides.rutgers.edu/datamanagement
§ Special Topics
Note that the following special topics are no longer covered by inperson workshops, but are available via screencast.
 Time Series in R: review of commands and techniques for basic time series analysis in R. Screencast at https://www.youtube.com/playlist?list=PLCj1LhGni3hOA2q0sfDNKBH9WIlLxXkbn and scripts at http://libguides.rutgers.edu/data_R
 Survival Analysis in R: review of commands and techniques for basic survival analysis in R. Scripts at http://libguides.rutgers.edu/data_R. Screencast at https://www.youtube.com/playlist?list=PLCj1LhGni3hOON9isnuVYIL8dNwkvwqr9.
 Big Data in Brief: an introduction to some of the techniques and software environments used to work with big data, with pointers to resources for further learning at http://libguides.rutgers.edu/bigdata. Screencast at https://www.youtube.com/playlist?list=PLCj1LhGni3hMNhIdrvz1F5JHIWi1qdX1
Data Visualization and R
Well, it has been a long time in coming, but I have finally finished converting my Data Visualization workshop series to a screencast video version. See this YouTube playlist for the complete series, and the materials at Github. This is the long version of the inperson 3 hour workshop. The video series goes into even more detail, starting from a history of major developments in visualization, to various implementations of specific graphs, interactive visualizations, web viz, big data, and more.
I also have some ideas for some more uptodate addins that I will probably record as lagniappe videos over the next few weeks. Those didn’t quite fit into the existing sequence of videos.
The energy to complete these videos came from several musical sources, of which I would credit Harmogu and Linton Kwesi Johnson as leading lights.
Statistical Software and Data Workshops Spring 2016
Rutgers University Libraries Data Services Workshop Series (New Brunswick)
January 2016
This Spring, Ryan Womack, Data Librarian, will repeat the series of workshops on statistical software, data visualization, and data management, as part of the Rutgers University Libraries Data Services. A detailed calendar and descriptions of each workshop are below. This semester each workshop topic will be repeated twice, once at the Library of Science and Medicine on Busch Campus, and once at Alexander Library on College Ave. These sessions will be identical except for location. Sessions will run approximately 3 hours. Workshops in parts will divide the time in thirds. For example, the first SPSS, Stata, and SAS workshop would start with SPSS at 12, Stata at 1, and SAS at 2. You are free to come only to those segments that interest you. There is no need to register, just come!
Logistics
Location: The Library of Science and Medicine (LSM on Busch) workshops will be held in the Conference Room on the 1st floor of LSM on Mondays from 12 to 3 pm. The Alexander Library (College Ave) workshops will be held in room 413 of the Scholarly Communication Center (4th floor of Alexander Library) from on Tuesdays from 1:10 to 4:10 pm.
For both locations, you are encouraged to bring your own laptop to work in your native environment. Alternatively, at Alexander Library, you can use a library desktop computer instead of your own laptop. At LSM, we will have laptops available to borrow for the session if you don’t bring your own. Room capacity is 25 in both locations, first come, first served.
If you can’t make the workshops, or would like a preview or refresher, screencast versions of many of the presentations are already available at http://libguides.rutgers.edu/data. Additional screencasts are continually being added to this series.
Calendar of workshops
Monday (LSM)
12 noon – 3 pm 
Tuesday (Alexander)
1:10 pm 4:10 pm 

January 25  Introduction to SPSS, Stata, and SAS  January 26 
February 1  Introduction to R  February 2 
February 8  Data Visualization in R  February 9 
February 15  Special Topics:
Time Series in R, Survival Analysis in R, Big Data in Brief 
February 16 
Description of Workshops:
§ Introduction to SPSS, Stata, and SAS (January 25 or January 26) provides overviews of these three popular commercial statistical software programs, covering the basics of navigation, loading data, graphics, and elementary descriptive statistics and regression using a sample dataset. If you are already using these packages with some degree of success, you may find these sessions too basic for you.
 SPSS is widely used statistical software with strengths in survey analysis and other social science disciplines. Copies of the workshop materials, a screencast, and additional SPSS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208425. SPSS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SPSS is also available in campus computer labs and via the Apps server (see below).
 Stata is flexible and allows relatively easy access to programming features. It is popular in economics among other areas. Copies of the workshop materials, a screencast, and additional Stata resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208427. Stata is made available by OIRT via campus license with no additional charge to install for Rutgers users. Find it at software.rutgers.edu.
 SAS is a powerful and longstanding system that handles large data sets well, and is popular in the pharmaceutical industry, among other applications. Copies of the workshop materials, a screencast, and additional SAS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208423. SAS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SAS is also available in campus computer labs, online via the SAS University Edition cloud service, and via the Apps server (see below).
Note: Accessing software via apps.rutgers.edu
SPSS, SAS, Stata, and R are available for remote access on apps.rutgers.edu. apps.rutgers.edu does not require any software installation, but you must activate the service first at netid.rutgers.edu.
§ Introduction to R (February 1 or February 2) – This session provides a threepart orientation to the R programming environment. R is freely available, open source statistical software that has been widely adopted in the research community. Due to its open nature, thousands of additional packages have been created by contributors to implement the latest statistical techniques, making R a very powerful tool. No prior knowledge is assumed. The three parts cover:
 Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
 Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
 Data Manipulation: data import and transformation, additional methods for working with large data sets
Additional R resources, including handouts, scripts, and screencast versions of the workshops, can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Data Visualization in R (February 8 or February 9) discusses principles for effective data visualization, and demonstrates techniques for implementing these using R. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background. The three parts are:
 Principles & Use in lattice and ggplot2: discusses classic principles of data visualization (Tufte, Cleveland) and illustrates them with the use of the lattice and ggplot2 packages. Some of the material here overlaps with Intro to R, pt 2, but at a higher level.
 Miscellany of Methods: illustrates a wide range of specific graphics for different contexts
 3D, Interactive and Big Data: presentation of 3D data, interactive exploration data, and techniques for large datasets
Additional R resources can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Special Topics (February 15 or February 16) covers a few different specialized areas. The three parts presented during the afternoon workshop are not related.
 Time Series in R: review of commands and techniques for basic time series analysis in R. Scripts at http://libguides.rutgers.edu/data_R
 Survival Analysis in R: review of commands and techniques for basic survival analysis in R. Scripts at http://libguides.rutgers.edu/data_R
 Big Data in Brief: an introduction to some of the techniques and software environments used to work with big data, with pointers to resources for further learning at http://libguides.rutgers.edu/bigdata
Of related interest: There is also a Digital Humanities Workshop Series this spring, covering topics including text analysis, network analysis, and digital mapping. See https://dh.rutgers.edu/spring2016workshops/ for information on the topics and schedule.
Data Workshops Full, Registration Closed
Somehow the response this Fall was much higher than expected, so all data and statistical software workshop sessions are now full and registration is closed. Please consult the screencasts, scripts, and handouts at libguides.rutgers.edu/data for a selfguided version of the same material.
The same sessions will run again live in the Spring.
Statistical Software and Data Workshops – Fall 2015
Rutgers University Libraries Data Services Workshop Series (New Brunswick)
August 2015
This Fall, Ryan Womack, Data Librarian, will give a series of workshops on statistical software, data visualization, and data management, as part of the Rutgers University Libraries Data Services. To go directly to the registration page, click here. A detailed calendar and descriptions of each workshop are below. This semester each workshop topic will be repeated twice, once at Alexander Library on College Ave, and once at the Library of Science and Medicine on Busch. These sessions will be identical except for location. Sessions will run approximately 3 hours. Workshops in parts will divide the time in thirds. For example, the SPSS, Stata, and SAS workshop would start with SPSS at 1:10, Stata at 2:10, and SAS at 3:10. You are free to come only to those segments that interest you.
Logistics
Location: The Alexander Library (College Ave) workshops will be held in room 415 of the Scholarly Communication Center (4th floor of Alexander Library) from on Wednesdays from 1:10 to 4:10 pm. The Library of Science and Medicine (LSM on Busch) workshops will be held in the Conference Room on the 1st floor of LSM on Thursdays from 12 to 3 pm. Pay attention to the different locations and times when signing up.
For both locations, you are encouraged to bring your own laptop to work in your native environment. Alternatively, at Alexander Library, you can use a library desktop computer instead of your own laptop. At LSM, we will have laptops available to borrow for the session if you don’t bring your own. Room capacity is 25 in both locations.
If you can’t make the workshops, or would like a preview or refresher, screencast versions of many of the presentations are already available at http://libguides.rutgers.edu/data. Additional screencasts are continually being added to this series.
Calendar of workshops
Wednesday (Alexander)
1:104:10 pm 
Thursday (LSM)
123 pm 

September 9  Introduction to SPSS, Stata, and SAS  September 10 
September 16  Introduction to R  September 17 
October 7  Data Visualization in R  September 24 
October 14  Special Topics:
Time Series in R, Survival Analysis in R, Big Data in Brief 
October 8 
Register for the workshops here
Description of Workshops:
§ Introduction to R (September 16 or September 17) – This session provides a threepart orientation to the R programming environment. R is freely available, open source statistical software that has been widely adopted in the research community. Due to its open nature, thousands of additional packages have been created by contributors to implement the latest statistical techniques, making R a very powerful tool. No prior knowledge is assumed. The three parts cover:
 Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
 Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
 Data Manipulation: data import and transformation, additional methods for working with large data sets
Additional R resources, including handouts, scripts, and screencast versions of the workshops, can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Introduction to SPSS, Stata, and SAS (September 9 or September 10) provides overviews of these three popular commercial statistical software programs, covering the basics of navigation, loading data, graphics, and elementary descriptive statistics and regression using a sample dataset. If you are already using these packages with some degree of success, you may find these sessions too basic for you.
 SPSS is widely used statistical software with strengths in survey analysis and other social science disciplines. Copies of the workshop materials, a screencast, and additional SPSS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208425. SPSS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SPSS is also available in campus computer labs and via the Apps server (see below).
 Stata is flexible and allows relatively easy access to programming features. It is popular in economics among other areas. Copies of the workshop materials, a screencast, and additional Stata resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208427. Stata is made available by OIRT via campus license with no additional charge to install for Rutgers users. Find it at software.rutgers.edu.
 SAS is a powerful and longstanding system that handles large data sets well, and is popular in the pharmaceutical industry, among other applications. Copies of the workshop materials, a screencast, and additional SAS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208423. SAS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SAS is also available in campus computer labs, online via the SAS University Edition cloud service, and via the Apps server (see below).
Note: Accessing software via apps.rutgers.edu
SPSS, SAS, Stata, and R are available for remote access on apps.rutgers.edu. apps.rutgers.edu does not require any software installation, but you must activate the service first at netid.rutgers.edu.
§ Data Visualization in R (October 7 or September 24) discusses principles for effective data visualization, and demonstrates techniques for implementing these using R. Some prior familiarity with R is assumed (packages, structure, syntax), but the presentation can be followed without this background. The three parts are:
 Principles & Use in lattice and ggplot2: discusses classic principles of data visualization (Tufte, Cleveland) and illustrates them with the use of the lattice and ggplot2 packages. Some of the material here overlaps with Intro to R, pt 2, but at a higher level.
 Miscellany of Methods: illustrates a wide range of specific graphics for different contexts
 3D, Interactive and Big Data: presentation of 3D data, interactive exploration data, and techniques for large datasets
Additional R resources can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Special Topics (October 14 or October 8) covers a few different specialized areas. The three parts presented during the afternoon workshop are not related.
 Time Series in R: review of commands and techniques for basic time series analysis in R. Scripts at http://libguides.rutgers.edu/data_R
 Survival Analysis in R: review of commands and techniques for basic survival analysis in R. Scripts at http://libguides.rutgers.edu/data_R
 Big Data in Brief: an introduction to some of the techniques and software environments used to work with big data, with pointers to resources for further learning at http://libguides.rutgers.edu/bigdata
HandsOn Big Data Workshop Screencasts
Screencasts from my IASSIST workshop on HandsOn Big Data at this year’s annual conference are now available at
http://libguides.rutgers.edu/bigdata
I’ll follow this up with a post that reflects on Big Data in more detail.
Statistical Software and Data Workshops – Spring 2015
Rutgers University Libraries Data Services Workshop Series (New Brunswick)
January 2015
This Spring, Ryan Womack, Data Librarian, will give a series of workshops on statistical software, data visualization, and data management, as part of the Rutgers University Libraries Data Services. To go directly to the registration page, click here. A detailed calendar and descriptions of each workshop are below.
Logistics
All workshops for Spring 2015 will be held in the Conference Room on the 1st floor of the Library of Science and Medicine (Busch Campus). Workshops are held on Wednesday afternoons from 3:20 to 4:40 pm or Thursday afternoons from 1:40 to 3:00 pm. The Wednesday series covers many aspects of the R open source statistical software environment. The early Thursday sessions are introductions to commerical statisical software (SPSS, Stata, SAS). Later in the semester, the Thursday sessions will cover several aspects of research data management.
You are encouraged to bring your own laptop for these sessions. Laptops are also available for borrowing during the workshops. Room capacity is approximately 25. SPSS, Stata, and SAS sessions will use the apps.rutgers.edu remote system.
If you can’t make the workshops, or would like a preview or refresher, screencast versions of many of the presentations are already available at http://libguides.rutgers.edu/data. Additional screencasts are continually being added to this series.
Calendar of workshops
Wednesday  Thursday  
Jan 28  Intro to R, part I, Statistical Functions  Intro to SPSS  Jan 29  
Feb 4  Intro to R, part II, Graphics  Intro to Stata  Feb 5  
Feb 11  Intro to R, part III, Data Manipulation  Intro to SAS  Feb 12  
Feb 18  Data Visualization, part I, Principles & Use in lattice and ggplot2  
Feb 25  Data Visualization, part II, Miscellany of Methods  Best Practices for Managing your Research Data  Feb 26  
March 4  Data Visualization, part III, 3D, Interactive and Big Data  Data Management Plans, Data Sharing and Archiving  March 5  
March 11  Survival Analysis in R  Reproducible Research  March 12  
March 25  Time Series in R 
Register for the workshops here
Description of Workshops:
§ Introduction to R (Jan 28, Feb 4, and Feb 11) – This 3part series provides an orientation to the R programming environment. R is freely available, open source statistical software that has been widely adopted in the research community. Due to its open nature, thousands of additional packages have been created by contributors to implement the latest statistical techniques, making R a very powerful tool. No prior knowledge is assumed. The three parts cover:
(Jan 28) Part I – Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
(Feb 4) Part II – Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
(Feb 11) Part III – Data Manipulation: data import and transformation, additional methods for working with large data sets
Additional R resources, including handouts, scripts, and screencast versions of the workshops, can be found here: http://libguides.rutgers.edu/data_R
R is freely downloadable from http://rproject.org
§ Introduction to SPSS (Jan 29) provides a single session overview of navigating the basics of SPSS. SPSS is widely used statistical software with strengths in survey analysis and other social science disciplines. If you are already using SPSS with some degree of success, this session may be too basic for you.
Copies of the workshop materials, a screencast, and additional SPSS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208425
SPSS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SPSS is also available in campus computer labs and via the Apps server (see below).
§ Introduction to Stata (Feb 5) provides a single session overview of navigating the basics of Stata. Stata is flexible and allows relatively easy access to programming features. It is popular in economics among other areas. If you are already using Stata with some degree of success, this session may be too basic for you.
Copies of the workshop materials, a screencast, and additional Stata resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208427
Stata is made available by OIRT via campus license with no additional charge to install for Rutgers users. Find it at software.rutgers.edu.
§ Introduction to SAS (Feb 12) provides a single session overview of navigating the basics of SAS. SAS is a powerful and longstanding system that handles large data sets well, and is popular in the pharmaceutical industry, among other applications. If you are already using SAS with some degree of success, this session may be too basic for you.
Copies of the workshop materials, a screencast, and additional SAS resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208423
SAS is made available by OIRT at a discounted academic rate, currently $100/academic year. Find it at software.rutgers.edu. SAS is also available in campus computer labs, online via the SAS University Edition cloud service, and via the Apps server (see below).
Note: Accessing software via apps.rutgers.edu
SPSS, SAS, Stata, and R are available for remote access on apps.rutgers.edu. apps.rutgers.edu does not require any software installation, but you must activate the service first at netid.rutgers.edu.
On Wednesdays, the R series will continue, including:
§ Data Visualization in R in 3 parts (basics, more methods, interactive & big data)
§ Time Series in R
§ Survival Analysis in R
On Thursdays, other topics in Data Management will be addressed, including:
§ Data Management Best Practices
§ Data Management Plans, Data Sharing and Archiving
§ Reproducible Research
Additional data management resources can be found here: http://libguides.rutgers.edu/datamanagement
Logistics, again
To repeat, All workshops for Spring 2015 will be held in the Conference Room on the 1st floor of the Library of Science and Medicine (Busch Campus) on Wednesday afternoons (starting at 3:20) and Thursday afternoons (starting at 1:40). Bring your own laptop if you can, although there will be laptops available to borrow.
Recent Comments