Monthly Archives: September, 2013

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.eduapps.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.

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