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Tutorials

The tutorials presented here provide a general introduction to various software packages, and are not intended to be a substitute for a full semester course, nor are they intended to replace the software's original documentation. Complete manuals for most programs are available through the University of Texas Perry Castaneda Library; you can check their availability through UTNETCAT. Most materials presented in the tutorials were developed for use in three hour lecture-format workshops taught every semester to interested UT students, faculty, and staff. Outside tutorials can be found in our Outside Resources section.

Mathematical Software Tutorials

Matlab
An overview of commands available in Matlab can be accessed through an online tutorial. In addition, the following is a collection of Matlab m files that should be useful in providing some practice in working with Matlab.

Matlab short course: The two files course.m and the squarex.m are ASCII files, contained within course.m are instructions for its use.You will need to download both, since course.m calls squarex.m. They must be downloaded into a directory in Matlab's search path, then accessed by typing 'course' at the Matlab command prompt or calling squarex.

No prior knowledge of Matlab or any mathematical software is assumed. This course will cover the basic aspects of Matlab such as statement syntax, mathematical operations and graphics, as well as some system interactions such as saving and printing your files. This course assumes a basic familiarity with matrices.

On-line tutorials are also available from The Mathworks, Inc., the developer of Matlab:

* Getting Started (HTML or PDF)
* Learning Matlab 7 (PDF)

Maple
Maple is a mathematical software package for symbolic computation. Conventional mathematical software packages usually require numerical values for all variables. In contrast, Maple can evaluate both symbolic and numerical expressions.

This UT Maple tutorial is designed for beginning Maple users. No prior knowledge of Maple or any symbolic mathematical software is assumed. It will cover the basic aspects of Maple such as statement syntax, mathematical operations and graphics. While this tutorial will deal with some calculus related material, it is designed so that anyone with a basic algebra background will benefit from it.

For more information about Maple, there are advanced Maple tutorials provided by Maplesoft . We also provide a basic Maple Programming tutorial from ETH-Zürich in PDF format.

Mathematica
An extensive documentation of Mathematica commands can be accessed through the help browser provided along with Mathematica.

tut.nb is a Mathematica notebook that has been found to be useful as a mathematica tutorial. The tutorial in it will cover the basic aspects of Mathematica such as statement syntax, mathematical operations and graphics, as well as some system interactions such as saving and printing your files.

While this tutorial will deal with some calculus related material, it is designed so that anyone with a basic algebra background will benefit from it. No prior knowledge of Mathematica or any symbolic mathematical software is assumed.

The procedures for launching Mathematica and loading notebooks are detailed in the Getting Started With Mathematica document.

If your browser is properly configured Mathematica will be automatically started with the notebook you select. Configuration instructions are currently available for the following browsers:

 

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Statistical Software Tutorials

AMOS
The AMOS (Analysis of Moment Structures) software program features a powerful, yet easy to use graphical interface. It is designed primarily for structural equation modeling and similar analyses (e.g., path analysis, confirmatory factor analysis), though it can also be used to fit MANOVA, MANCOVA, ANOVA, ANCOVA, and regression models.

HLM
HLM (Hierarchical Linear Models) are used for analyzing data in a clustered or "nested" structure, in which lower-level units of analysis are nested within higher-level units of analysis. For example, students are nested within classrooms, which are nested within schools. While experimenters are often not interested in the effects of a particular classroom or school when they are examining the effects of a classroom intervention, these units potentially have an effect on the outcome of the study that should be accounted for in a statistical model. The program can be used to analyze a variety of questions using either categorical or continuous dependent variables.

PRELIS and LISREL
PRELIS and LISREL are designed primarily for structural equation modeling and similar analyses (e.g., confirmatory factor analysis and path analysis), though it can also be used to fit ANOVA, ANCOVA, MANOVA, and MANCOVA models. Also, it be used to perform regression analysis and some multilevel or hierarchical linear modeling (HLMs). Many of the statistical methods are also now available for the analysis of complex sampling designs.

Mplus
Mplus is primarily designed for conducting exploratory factor analysis, confirmatory factor analysis, and structural equation modeling. The program can also handle multiple group analysis and multilevel SEM.

SAS
Over the years SAS has developed a reputation of being a powerful and full-featured package for general statistical analysis. The new release of SAS (version 8) has a number of new features that promise to make SAS more user-friendly. In particular, the current version of SAS has a substantially enhanced windows-driven interface which allows you to point and click your way through many tasks that previously required knowledge of SAS programming syntax.

SPSS

Getting Started: introduces readers to the SPSS for Windows environment, and discusses how to create or import a dataset, transform variables, manipulate data, and perform descriptive statistics.

Descriptive and Inferential Statistics: describes the use of SPSS to obtain descriptive and inferential statistics. In this module, you will be introduced to procedures used to obtain several descriptive statistics, frequency tables, and crosstabulations in the first section. In the second section, the Chi-square test of independence, independent and paired sample t tests, bivariate and partial correlations, regression, and the general linear model will be covered.

Displaying Data: describes the use of SPSS to create and modify tables which can be exported to other applications. Graphical displays of data are also discussed, including bar graphs and scatterplots as well as a discussions on how to modify graphs using the SPSS Chart Editor and Interactive Graphs.

Data Manipulation and Advanced Topics: describes the use of SPSS to do advanced data manipulation such as splitting files for analyses, merging two files, aggregating datasets, and combining multiple tables in a database into an SPSS dataset. Several advanced topics are also included, such as the use of SPSS syntax, the SPSS Visual Basic editor, and SPSS Macros.

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Last updated May 2, 2007.
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