Mathematical theory is critical for developing an understanding of the subject matter and the dynamics involved. However, from an applied perspective, it becomes necessary to use computing tools to effectively leverage mathematical theory and use mathematical formulae to efficiently collect, manage, analyze and process data. This page focuses on basic software tools that can be used for managing numbers – it is a general software resource page covering quantitative applications across courses and is expected to be useful for all ranges of users: beginners – intermediate – expert and everything in between!

Excel: This page will have a heavy emphasis on Microsoft Excel. This is due to multiple reasons:

  1. Excel is a universally present software – very easy to get started with.
  2. Excel can be used for a wide range of data management, analysis, processing and modeling categories and is therefore one of the most flexible tools.
  3. A lot of work has already been done in Excel and hence there are ready modules for a wide variety of requirements
  4. Businesses and corporations, including financial and educational institutions, use Excel extensively and Excel is therefore a strong plus for career development
  5. Excel works well for the beginner for basic purposes and it works very well for advanced users with sophisticated modeling requirements (and so also for everyone in between and around!).

Here are a few links to get you started:

1. GCF –This website gives you basic tutorials with YouTube videos for Excel 2010.

2. Chandoo Basics –This website also gives you basic Excel skills with YouTube videos.

3. Add-ins –“Add-in” is a software that adds features into Excel. This website provides many useful add-ins.

4. Contextures –This website gives you Excel tips and tutorials via index.

5. More –This website provides useful free websites for Excel tutorials including the websites listed above.

A good set of Excel Models for Stats!

For the use of Excel for basic statistic calculations, check out the resources here.


R: R is a very versatile and powerful free software environment for statistical computing and data analysis – it has very valuable data visualization tools as well. It works on a wide variety of UNIX platforms, Windows and MacOS and though it is mainly driven by coding, yet menu driven options such as R commander are readily available for those starting of. The official website for R: http://www.r-project.org/


SPSS:    Here are some popular tutorial links for SPSS:

Lynda’s SPSS
Datastep Training
SPSS Videos
Open EDu

Practice is critical, the more time you spend on SPSS software, the easier (relatively) it gets!

General Notes on Statistics: