Research Guides: *Data Science (SPS): Analytic Tools

Analytic Software Packages

R
R is an open source software package for statistical computing and graphing.
SAS
SAS is a commercial analytic software program. Copies of this software package can be purchased.
SPSS
SPSS is a commercially available analytic tool. A copy of the software can be purchased through the University's NUIT.

Additional Help with Analytical Tools

Resources for Data Analysis Research Guide
This extensive guides provides information, tutorials, and link to books about R, SAS, SPSS, and other analytic tools.

LinkedIn Learning (formerly Lynda.com)

LinkedIn Learning (formerly Lynda.com)
Northwestern University and lynda.com have partnered to offer University students, faculty and staff unlimited, on-demand access to a full library of online courses at no additional cost. Course topics include most major software programs as well as workplace skills like presentations, leadership and career development.

Introductory Text on Various Analytic Tools

A Beginner's Guide To R by Alain F. Zuur, Elena N. Ieno, Erik H.W.G. Meesters
ISBN: 9780387938363
Table of Contents:
Introduction / Alain F. Zuur, Elena N. Ieno, Erik Meesters
Getting Data into R / Alain F. Zuur, Elena N. Ieno, Erik Meesters
Accessing Variables and Managing Subsets of Data / Alain F. Zuur, Elena N. Ieno, Erik Meesters
Simple Functions / Alain F. Zuur, Elena N. Ieno, Erik Meesters
An Introduction to Basic Plotting Tools / Alain F. Zuur, Elena N. Ieno, Erik Meesters
Loops and Functions / Alain F. Zuur, Elena N. Ieno, Erik Meesters
Graphing Tools / Alain F. Zuur, Elena N. Ieno, Erik Meesters
An Introduction to the Lattice Package / Alain F. Zuur, Elena N. Ieno, Erik Meesters -- Common R Mistakes / Alain F. Zuur, Elena N. Ieno, Erik Meesters
Data Manipulation with R by Phil Spector
ISBN: 9780387747309
Table of Contents:
Data in R
Reading and Writing Data
R and Databases
Dates
Factors
Subscripting
Character Manipulation
Data Aggregation
Reshaping Data
A Handbook of Statistical Analyses Using R by Brian S. Everitt and Torsten Hothorn
ISBN: 9781420079333
Table of Contents:
1. An Introduction to R
2. Data Analysis Using Graphical Displays
3. Simple Inference
4. Conditional Inference
5. Analysis of Variance
6. Simple and Multiple Linear Regression
7. Logistic Regression and Generalised Linear Models
8. Density Estimation
9. Recursive Partitioning
10. Smoothers and Generalised Additive Models
11. Survival Analysis
12. Analysing Longitudinal Data I
13. Analysing Longitudinal Data II
14. Simultaneous Inference and Multiple Comparisons
15. Meta-Analysis
16. Principal Component Analysis
17. Multidimensional Scaling
18. Cluster Analysis.
Data Mining with R: Learning with Case Studies by Luis Torgo
ISBN: 9781439810187
SAS and R: Data Management, Statistical Analysis, and Graphics by Ken Kleinman and Nicholas J. Horton
ISBN: 9781420070576
Using R for Introductory Statistics by John Verzani
ISBN: 1584884509