U.S. County-Level Natality and Mortality Data, 1915-2007
Another new release from ICPSR that is too interesting not to mention. The U.S. County-Level Natality and Mortality Data, 1915-2007 has nearly a century of detailed data on births and infant deaths for those looking for long-term patterns.
National Crime Victimization Survey, Concatenated File, 1992-2015
The National Crime Victimization Survey is published every year, but the Concatenated File 1992-2015 allows easy multi-year comparisons of data. From ICPSR, try it out!
Replication Crisis…
This article discusses replication and data sharing in the context of the biggest clinical trial ever, on deworming in India. Fascinating stuff.
Hands-On Big Data Workshop Screencasts
Screencasts from my IASSIST workshop on Hands-On 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, 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.
Data Viz and other techniques in R
Registration is now open for the remainder of the continuing Fall Data Workshop series, presented by Ryan Womack, Data Librarian.
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 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.
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.
Description of Workshops:
§ Data Visualization in R (Sept 30, Oct 7, Oct 14) 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:
(Sept 30) Part I – 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.
(Oct 7) Part II – Miscellany of Methods: illustrates a wide range of specific graphics for different contexts
(Oct 14) Part III – 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
§ Time Series in R (Oct 21)
Review of commands and techniques for basic time series analysis in R
§ Survival Analysis in R (Oct 28)
Review of commands and techniques for basic survival analysis in R
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.
Statistical Software Workshops – Fall 2013
Rutgers University Libraries Data Services Workshop Series (New Brunswick)
Fall 2013
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.
Logistics
All workshops for Fall 2013 will be held in the Teleconference Lecture Hall on the 4th floor of Alexander Library (169 College Avenue). Workshops are held on Tuesdays and Thursdays from 7-8:30 pm according to the schedule below. On two dates, indicated with *, we will start at 7:15 instead of 7. These are open workshops, registration is not necessary.
This room does not have its own computers. You can bring your laptop if you want to follow along with the exercises, but this is not required.
Screencast versions of the presentations will be made available about the same time as the workshop dates at http://libguides.rutgers.edu/data.
Calendar of workshops
|
Tuesday |
|
Thursday |
|
Sept 17 |
Intro to R, part I Statistical Functions |
|
Intro to SPSS |
Sept 19 |
Sept 24 |
Intro to R, part II Graphics |
|
Intro to SAS |
Sept 26 |
Oct 1 |
Intro to R, part III Data Manipulation |
|
Intro to Stata |
Oct 3* (starts at 7:15) |
|
|
|
Data Visualization, part I, Principles & Use in lattice and ggplot2 |
Oct 10 |
Oct 15 |
Time Series in R |
|
Data Visualization, part II Miscellany of Methods |
Oct 17 |
|
|
|
Data Visualization, part III, 3-D, Interactive and Big Data |
Oct 24* (starts at 7:15) |
Oct 29 |
Best Practices for Managing your Research Data |
|
|
|
Description of Workshops:
§ Introduction to R (Sept 17, Sept 24, and Oct 1) – 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 17) Part I – Statistical Techniques: getting around in R, descriptive statistics, regression, significance tests, working with packages
(Sept 24) Part II – Graphics: comparison of graphing techniques in base R, lattice, and ggplot2 packages
(Oct 1) Part III – Data Manipulation: data import and transformation, additional methods for working with large data sets
Additional R resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208422
R is freely downloadable from http://r-project.org
§ Introduction to SPSS (Sept 19) 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 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 SAS (Sept 26) 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 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).
§ Introduction to Stata (Oct 3) 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 SAS with some degree of success, this session may be too basic for you.
Copies of the workshop materials 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.
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 (Oct 10, Oct 17, Oct 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:
(Oct 10) Part I – 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.
(Oct 17) Part II – Miscellany of Methods: illustrates a wide range of specific graphics for different contexts
(Oct 24) Part III – 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/content.php?pid=115296&sid=1208422
R is freely downloadable from http://r-project.org
§ Time Series in R (Oct 15) is a special topics session covering the use of functions that analyze time series in R. Content roughly parallels the material presented in more detail in the book Introductory Time Series with R (available via SpringerLink).
Additional R resources can be found here: http://libguides.rutgers.edu/content.php?pid=115296&sid=1208422
R is freely downloadable from http://r-project.org
§ Data Management Best Practices (Oct 29) 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/data,management
Logistics, again
To repeat, all workshops will be held in the Teleconference Lecture Hall on the 4th floor of Alexander Library (169 College Avenue). Workshops run from 7-8:30 pm (except for the two delayed starts indicated in the table above).
These are open workshops, registration is not necessary.
Screencast versions of the presentations will be made available about the same time as the workshop dates at http://libguides.rutgers.edu/data.
Statistical Software Workshops – Extra Sessions – Spring 2013
The interest in the series has surpassed all of the Libraries’ expectations and experiences in prior semesters. The only space available for this workshop on Busch campus has approximately 30 seats, but we have well over 100 registrations for each session.
In order to accommodate the extra demand, I will be offering extra sessions on consecutive Monday mornings, from 10:30 am to noon.
These will be held in Alexander Library on the College Avenue campus, in the 4th floor teleconference lecture hall. This room has seating for 98, so I anticipate that we will be able to accomodate everyone.
I wanted to emphasize a few points. Although the announcement was picked up by some of the official Rutgers listservs, these workshops are not official or required and carry no credits or certificates of completion. They are introductions to help you get started with using the software. The SAS and SPSS sessions in particular focus on navigating around the software for new users. If you have used these packages before, you may not benefit much from the workshops.
The workshop materials are also available online at
http://libguides.rutgers.edu/content.php?pid=115296&sid=1208421
Take a look at these to decide if you would benefit from attending.
Once again, all extra sessions will be
Mondays, 10:30 am – noon
4th floor Teleconference Lecture Hall
Alexander Library, College Avenue Campus
The dates for each workshop are
Jan. 28 – Introduction to SPSS
Feb. 4 – Introduction to SAS
Feb. 11 – Introduction to R (part 1- Basic Statistics)
Feb. 18 – Introduction to R (part 2 – Graphics)
Feb. 25 – Introduction to R (part 3 – Data Manipulation)
March 4 -Time Series in R
Please come to the Alexander morning sessions if at all possible!
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