Statistical Software and Data Workshops, Fall 2018
New Brunswick Libraries Data Workshop Series
Fall 2018
This Fall, Ryan Womack, Data Librarian, will offer a series of workshops on statistical software and data visualization as part of New Brunswick Libraries Data Management Services. A detailed calendar and descriptions of each workshop are below. The workshop on reproducible research is moving online to YouTube – stay tuned for an upcoming blog post and announcement on its availability. We also anticipate offering additional workshops through the Graduate Specialist program. That announcement will be coming in September.
This semester each workshop topic will be repeated twice in person, 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 1:10-4:10 pm) would start with SPSS at 1:10 pm, Stata at 2:10 pm, and SAS at 3:10 pm. You are free to come only to those segments that interest you. There is no need to register, just come! A
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 https://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 |
|
| October 3 | Introduction to SPSS, Stata, and SAS | September 13 |
| October 10 | Introduction to R | September 20 |
| October 17 | Data Visualization in R | September 27 |
Description of Workshops:
§ Introduction to SPSS, Stata, and SAS (September 13 or October 3) 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 long-standing 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 20 or October 10) – This session provides a three-part 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://r-project.org
§ Data Visualization in R (September 27 or October 17) 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
- 3-D, Interactive, and Big Data: presentation of 3-D 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://r-project.org
Note that the following special topics are no longer covered by in-person workshops, but are available via screencast.
- Reproducible Research – [Coming Soon] how to create data, code, and publications in open, reusable formats and maximize the impact and validity of your research.
- 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=PLCj1LhGni3hMNhIdrvz1F5-JHIWi1qdX1
Statistical Software and Data Workshops, Spring 2018
New Brunswick Libraries Data Workshop Series
Spring 2018
This Spring, Ryan Womack, Data Librarian, will repeat the series of workshops on statistical software and data visualization as part of New Brunswick Libraries Data Management Services. A detailed calendar and descriptions of each workshop are below. The workshop on reproducible research is moving online to YouTube – stay tuned for an upcoming blog post and announcement on its availability.
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 12-3 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 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 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
| Monday (LSM)
12 noon – 3 pm |
Tuesday (Alexander)
1:10 pm -4:10 pm |
|
| January 29 | Introduction to SPSS, Stata, and SAS | January 30 |
| February 5 | Introduction to R | February 6 |
| February 12 | Data Visualization in R | February 13 |
Description of Workshops:
§ Introduction to SPSS, Stata, and SAS (January 29 or January 30) 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 long-standing 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 (February 5 or February 6) – This session provides a three-part 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://r-project.org
§ Data Visualization in R (February 12 or February 13) 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
- 3-D, Interactive, and Big Data: presentation of 3-D 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://r-project.org
Note that the following special topics are no longer covered by in-person workshops, but are available via screencast.
- Reproducible Research – [Coming Soon] how to create data, code, and publications in open, reusable formats and maximize the impact and validity of your research.
- 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=PLCj1LhGni3hMNhIdrvz1F5-JHIWi1qdX1
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 12-3 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 long-standing 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 three-part 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://r-project.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
- 3-D, Interactive, and Big Data: presentation of 3-D 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://r-project.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 in-person 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=PLCj1LhGni3hMNhIdrvz1F5-JHIWi1qdX1
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 12-3 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 long-standing 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 three-part 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://r-project.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
- 3-D, Interactive, and Big Data: presentation of 3-D 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://r-project.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 in-person 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=PLCj1LhGni3hMNhIdrvz1F5-JHIWi1qdX1
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 long-standing 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 three-part 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://r-project.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
- 3-D, Interactive and Big Data: presentation of 3-D 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://r-project.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/spring-2016-workshops/ 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 self-guided 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)
1:10-4:10 pm |
Thursday (LSM)
12-3 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 three-part 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://r-project.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 long-standing 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
- 3-D, Interactive and Big Data: presentation of 3-D 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://r-project.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
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, 3-D, 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 3-part 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://r-project.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 long-standing 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.
Data Management Workshop Series
The final component of the Fall Data Workshop series are three workshops on aspects of data management, presented by Ryan Womack, Data Librarian, and Aletia Morgan, Research Data Manager at Rutgers University Libraries.
To go directly to the registration page for this series, click here. A detailed calendar and descriptions of each workshop are below.
Logistics
Data management workshops for Fall 2014 will be held in Room 413 on the 4th floor of Alexander Library (169 College Avenue). Workshops are held on Thursdays from 1:10-2:30 pm according to the schedule below. Room capacity is limited to 25.
Description of Workshops:
§ Best Practices for Managing Your Data (Oct 9)
This workshop is targeted to graduate students who are generating data for their own research. The session discusses 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.
Additional data management resources can be found here: http://libguides.rutgers.edu/datamanagement
§ Data Management Plans, Data Sharing and Archiving (Oct 23)
This workshop is 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. It reviews DMP guidelines, checklist, and general advice, along with options for sharing and permanently archiving research data.
§ Reproducible Research (Oct 30)
The workshop is targeted to any interested faculty and students who are interested in learning about the growing interest in making the products of research accessible and usable by others in order to verify, replicate, and extend research findings. It reviews how to plan research, to create publications, code, and data in open, reusable formats, and maximize the impact of shared research findings.
Statistical Software and Data Workshops – Fall 2014
Rutgers University Libraries Data Services Workshop Series (New Brunswick)
September 2014
This Fall, Ryan Womack, Data Librarian, will give a series of workshops on statistical software, data visualization, and data management, as part of the Libraries Data Services. This announcement outlines the schedule of workshops for the first weeks of September, and provides a preview of upcoming October events. To go directly to the registration page, click here. A detailed calendar and descriptions of each workshop are below.
Logistics
All workshops for Fall 2014 will be held in Room 413 on the 4th floor of Alexander Library (169 College Avenue). Workshops are held on Tuesdays and Thursdays from 1:10-2:30 pm according to the schedule below. Room capacity is limited to 25.
Room 413 has R installed on its workstations. You are also welcome to bring your laptop if you want to follow along with the exercises, but this is not required. 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 will be added for the newer workshops in the series.
Calendar of workshops
| Tuesday | Thursday | |||
| Sept 9 | Intro to R, part I, Statistical Functions | Intro to SPSS | Sept 11 | |
| Sept 16 | Intro to R, part II, Graphics | Intro to Stata | Sept 18 | |
| Sept 23 | Intro to R, part III, Data Manipulation | |||
| Sept 30 | Data Visualization, part I, Principles & Use in lattice and ggplot2 | Intro to SAS | Oct 2 | |
| Oct 7 | Data Visualization, part II, Miscellany of Methods | Best Practices for Managing your Research Data | Oct 9 | |
| Oct 14 | Data Visualization, part III, 3-D, Interactive and Big Data | Oct 16 | ||
| Oct 21 | Time Series in R | Data Management Plans, Data Sharing and Archiving | Oct 23 | |
| Oct 28 | Survival Analysis in R | Reproducible Research | Oct 30 |
Register for the workshops here
Description of Workshops:
§ Introduction to R (Sept 9, Sept 16, and Sept 23) – This 3-part 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:
(Sept 9) Part I – Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
(Sept 16) Part II – Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
(Sept 23) 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://r-project.org
§ Introduction to SPSS (Sept 11) 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 (Sept 18) 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 (Oct 2) provides a single session overview of navigating the basics of SAS. SAS is a powerful and long-standing 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 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.
In October, the workshops will continue at the same times (Tuesday and Thursday afternoons, 1:10-2:30), also in Alexander Library 413.
On Tuesdays, 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/data,management
Logistics, again
To repeat, all workshops will be held in room 413 on the 4th floor of Alexander Library (169 College Avenue). Workshops run from 1:10-2:30 pm.
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