Click on a software name to be taken to its tutorial(s).

Mathematical Software

IMSL Libraries , Matlab, Maple, Mathematica

Statistical Software

AMOS, HLM, PRELIS and LISREL, Mplus, SAS, SPSS

Mathematical Software Tutorials

IMSL Libraries

IMSL, which once stood for "International Mathematical and Statistical Libraries," is an extensive collection of mathematical and statistical subroutines and functions in the Fortran and C programming languages.  These subroutines and functions can be linked during compilation and called as embedded objects from a program or script written in the parent programming language as needed.  The content of the libraries ranges from commonly used mathematical techniques such as eigensystem analysis and optimization algorithms to special functions such as Bessel, Gamma, trignometric, and hyperbolic functions.  As libraries, the IMSL packages are not standalone applications.  Individual routines must be called from links compiled in external programs.

• IMSL Fortran Library Tutorial
• IMSL C Library Tutorial

Matlab

An overview of commands available in Matlab can be accessed through this 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 introductory exercise: Download matlab_tutorial_files.zip, a zipfile containing two files course.m and the squarex.m (course.m calls squarex.m). Contained within course.m are instructions for its use. They must be downloaded into a directory in Matlab's search path, and 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 tutorial covers 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.

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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 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.

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Mathematica

Getting Started: The procedures for launching Mathematica and loading notebooks are detailed in the this tutorial.  While it 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.

Download tut.zip, which contains tut.nb - 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.

Graphics Fundamentals: : Mathematica is capable of generating a wide range of graphics, from a simple plot of a function, to a three dimensional animation of complex physical systems. This document will concentrate on the most fundamental and most widely used of the Mathematica plotting capabilities, the use of the Plot function to generate two dimensional graphics.

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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.

Download wheaton-generated.zip to obtain the .sav and .xls versions of the input file needed for the tutorial.

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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.

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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.

Download LISRELtutorial.zip for use in the tutorial.

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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.

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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.

• SAS Analyst for MS Windows (Click HERE to download instructions for creating the dataset.)
• SAS I - Getting Started
• SAS II - Inferential Statistics

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.

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