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ACS Short Courses |
Computer Based Training |
Electronic Communications | Human Resources
Courses | CLEAR |
UNT Mini-courses | Central Web
Support Tutorials | EIS
Training
Academic Computing and User Services Short Courses
2010 Fall Short Course Offerings
Plans are underway to resume teaching some instructor-led courses this semester, but a final schecule has not been set. Also, a MAJOR change has taken place WRT SPSS and SAS courses; they are now offered online only . Another class available online is Introduction to R .
RSS staff will be still be available for consultation on those topics, however.
Click here to
see the sorts of classes that will most likely be offered this semester, including the new descriptions and links for SPSS and SAS.
Registration
Please pre-register to
attend. Please call or send mail to Claudia Lynch (940-565-4068,
lynch@unt.edu ) indicating what
classes you would like to attend.
Eligibility and
Class Size
Faculty and students
have first priority to register for these classes. A maximum of 15
people will be admitted to each of the courses.
Academic Computing Services reserves the right to cancel any course that
has 5 or fewer people registered 3 days before the course is scheduled.
Hands-on Classes
Course participation may require use of your EUID and password. If
you don't know your EUID and/or you haven't set your password, visit
http://ams.unt.edu/ .
Special classes can be
arranged with the RSS staff. See "Customized Short Courses" below for further
information. Also,
you can always contact the RSS staff for one-on-one
consultation. Please read the
FAQ before requesting
an appointment though.
Customized Short Courses
Faculty members can request customized short courses from ACS, geared
to their class needs. Other groups can request special courses also.
Contact ACS for more information (ISB 119, 565-4068,
lynch@unt.edu).
Especially for Faculty and Staff Members
In addition to the ACS Short Courses, which are available to
students, faculty and staff, staff and faculty members can take courses
offered through the
Human Resources
Department (they have a new comprehensive training curriculum), and the Center for
Learning Enhancement, Assessment, and Redesign. Additionally,
the Center for Continuing
Education and Conference Management offers a variety of courses,
usually for a small fee.
EIS training is available.
Questions or comments relating to EIS training should be sent to
EISTCA@unt.edu.
Microsoft E-Learning courses are now available
for faculty and staff via our
UNT-Microsoft Campus Agreement. Please contact
Claudia Lynch at
lynch@unt.edu for instructions on accessing
this training.
Microsoft Outlook Training and more
The Messaging Systems Group has all sorts of useful
information on their website, including
training information.
Central Web Support
Consult Central Web Support for assistance in acquiring
“Internet services and support.” As described on their
website:
CWS provides Internet services and support to UNT faculty, staff and
students. Services include allocating and assisting departments, campus
organizations and faculty with web space and associated applications.
Additionally, CWS assists web developers with databases and associated
web applications, troubleshooting problems, support and service.
Tutorials are available from CWS on a variety of
topics.
CLEAR (was Center for Distributed Learning)
CLEAR offers courses especially for Faculty
Members. A list of topics and further information can be found
here.
The center also offers a "Brown Bag" series which meets for lunch the
first Thursday of each month at Noon in Chilton 245. The purpose of this
group is to bring faculty members together to share their experiences
with distributed learning. One demonstration will be made at each
meeting by a faculty member with experience in distributed learning.
More information on these activities can be found at the
CLEAR Website.
Information Security Awareness
The UNT Information Security team has been offering
Information Security Awareness courses to all UNT faculty and staff. Topics to
be covered will include workstation security, sensitive data handling, copyright
infringement issues, identity theft, email security, and more.
For more
information, or if you would like to request a customized course to be taught
for your department, contact Gabe Marshall at x4062, or at
security@unt.edu.
Also, Information Security Training is
now available through
Blackboard Vista.
UNT Mini-Courses
There are a variety of courses offered, for a fee, to UNT faculty,
staff and students as well as the general public. For additional
information surf over to
http://www.unt.edu/minicourses/
Alternate Forms of Training
Many of the General Access Labs around campus have
tutorials installed on their computers. See
http://www.gal.unt.edu/ for a list
of labs and their locations. The Willis Library, for example, has a
list of Tutorials and Software Support.
The Training Website has
all sorts of information about alternate forms of training. Computer
Based Training (CBT) and Web-based training are some of the alternatives
offered.
For further information on CBT at UNT, see the CBT
website.
State of Texas Department of
Information Resources
Another possible source of training for staff and, perhaps,
faculty members is the Texas Department of Information Resources. A look at
their Education and Training
website reveals
some interesting possibilities.
Gartner Research Services
Not exactly training, but training could be involved depending
on the topic you are interested in.
Gartner Research
Services are available to UNT faculty, staff, and students. Gartner is now offering "Webinar Wednesdays." To view all the offerings see: the calendar You can also listen to Gartner podcasts here .
Statistical
Package/Research Courses
(1) SPSS Part 1: Introduction to SPSS Programming
-- This is a BEGINNING
COURSE that familiarizes users with basic techniques in SPSS for simple data processing tasks and is a starting point for those who want to use SPSS as their primary tool for data analysis and data management. This short course will cover opening the program, familiarization with the different windows and menus, importing data, creating data and specifying variable parameters, as well as frequencies and graphing, and descriptive statistics with more graphing. No prior experience with SPSS is assumed, but it is preferable to have background knowledge in file structures and system commands commonly used by most operating systems. This course is designed to be self-taught. All materials are available at:
http://www.unt.edu/rss/class/Jon/SPSS_SC/ If you have any questions concerning the content of the course or would like clarification of a topic covered in the course materials; please contact the course author listed on the bottom of the course page.
(2) SPSS Part 2: Intermediate SPSS -- Second in the SPSS series, this course builds on the concepts presented in the Introduction to SPSS Programming Course with emphasis on recoding an item, compute statements, replacing missing values, selecting cases, and merging data files. It covers the typical SPSS procedures and SPSS programming skills. Before taking this course, students should take or understand the concepts covered in "Introduction to SPSS Programming." This course is designed to be self-taught. All materials are available at:
http://www.unt.edu/rss/class/Jon/SPSS_SC/ If you have any questions concerning the content of the course or would like clarification of a topic covered in the course materials; please contact the course author listed on the bottom of the course page.
(3) SAS Part 1: Introduction to SAS Programming
-- This is a foundation course that introduces the basic programming techniques for using SAS to accomplish typical data processing tasks. This course is a starting point for those who want to use SAS as their primary research tool. This short course will cover opening the program, familiarization with the different windows and menus, importing data, and common procedures (PROC) for obtaining frequencies, descriptive statistics and common graphing. No prior programming knowledge is required but it is preferable to have background knowledge in file structures and system commands on Windows operating systems. This course is designed to be self-taught. All tutorials and data sets are available at:
http://www.unt.edu/rss/class/Jon/SAS_SC/ If you have any questions concerning the content of the course or would like clarification of a topic covered in the course materials; please contact the course author listed on the bottom of the course page.
(4) SAS Part 2 Intermediate SAS -- Second in the SAS series, this course builds on the concepts presented in the "Introduction to SAS Programming" course with emphasis on running SAS to conduct common inferential statistical procedures (e.g. t-tests, correlation, ANOVA, linear regression, principal components analysis, factor analysis, etc.). Before taking this course, students should take and understand the concepts covered in "Introduction to SAS Programming.” This course is designed to be self-taught. All tutorials and data sets are available at:
http://www.unt.edu/rss/class/Jon/SAS_SC/ If you have any questions concerning the content of the course or would like clarification of a topic covered in the course materials; please contact the course author listed on the bottom of the course page.
(5) Introduction to Stata -- This is a
foundation course that introduces the basic user interface techniques
for using Stata 8 to accomplish typical data processing tasks. Emphasis
will be placed on utilizing Stata 8's GUI interface and the Stata
command box. This course is a starting point for those who want to use
Stata as their primary research tool. No prior programming
knowledge is required but it is preferable to have background knowledge
in file structures and system commands on one of the following operating
systems: DOS and/or Windows.
One three-hour session to be held in Chilton Hall, Room 274:
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Date |
Time |
Instructor |
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2-5 p.m. |
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(6) Intermediate Stata -- This course is
designed for experienced Stata users who want to apply Stata programming
skills to their research projects and data analyses or those who have
specific questions about Stata functions. Before selecting this course,
students should complete the "Introduction to Stata" or have previous
experience with Stata. Applicants are encouraged to bring their
own data sets, although sample data will be provided.
One three-hour session to be held in Chilton Hall, Room 270:
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Date |
Time |
Instructor |
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2-5 p.m. |
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(7) New Technologies for Survey Research
-- This course aims to introduce researchers to new technologies for
conducting and administering
surveys. This course will focus on creating Web surveys using UNT's Zope
Web application server and HTML surveys. Topics will cover good
survey construction design practices and appropriate analysis methods
for survey data.
One three-hour session to be held in Chilton Hall, Room 270:
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Date |
Time |
Instructor |
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2-5 p.m. |
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(8) Applications in R: Latent Variable Modeling with Survey Data Part I -- Introduction to Latent Variable Models and Introduction to R language: a) Managing an R session -
changing R options; workspaces; saving and recalling programs, using a program editor, using a drop down menu; b) Fundamentals of R language -
reading in data, data constructs indexing and sub-setting data, conditional statements, looping over data; c) R Graphics -
graphical exploration of data, simple line plots, histograms, scatterplots and scatterplot matrices, conditioning plots; d) Examples of Linear Modeling in R -
Correlation, Regression, ANOVA; d) Robust Modeling in R (e.g. M-estimators for correlation and regression); e) Resampling Based Statistics in R -
Bagging approaches to model estimation (boostrap aggregation for model estimates).
Bring an empty USB portable drive so you can save your in-class work.
One three-hour session to be held in Chilton Hall, Room 270:
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Date |
Time |
Instructor |
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2-5 p.m. |
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(9) Applications in R: Latent Variable Modeling with Survey Data -- Part II
-- a) Exploratory Factor Analysis; b) Confirmatory Factor Analysis; c) Item Response Theory Modeling (IRT);
e) Missing Values Imputation; d) Causal Modeling Using Rubin’s Counterfactual Framework - Optimal Matching Algorithms,
Propensity Score Matching, Variance Estimation Using Random Groups Method (resampling based variance estimation methods).
Bring an empty USB portable drive so you can save your in-class work.
One three-hour session to be held in Chilton Hall, Room 270:
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Date |
Time |
Instructor |
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2-5 p.m. |
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Please Note: The University of North Texas will never
ask for personal information by e-mail. If you receive
an e-mail purporting to be from the University that asks for
personal information or account passwords, do not respond.
If there is any question regarding the authenticity of an
email, please contact UNT Information Security at (940)
369-7800.
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