Is Excel a Good Statistical Tool? Maybe Not…

A recent online discussion involving researchers from around the globe addressed the question of whether or not Microsoft Excel is a good statistical tool for analyzing data. While most agreed that Excel offers some standard analysis and graphing capabilities, many of the users had the opinion that the software is limited when it comes to larger data sets. Comments included the following:


From a PhD at the University of Applied Sciences and Arts Western Switzerland


I would not recommend using Excel for statistical analysis for the following reasons:


  1. It is difficult to know what Excel is truly doing when applying a formula.
  2. Excel has weird ways of handling missing data.
  3. Programming analysis in Excel is complicated and mistakes easily pass unnoticed.


From a PhD at the University of Calgary, Canada


  1. Excel can easily mess up date fields.
  2. Be careful when sorting in Excel (columns can be sorted independently).
  3. It is difficult to share what you have done in a simple, compact manner. When I’m handed a complicated analysis completed by someone else using Excel, it can be difficult to tease out what they have done.


From a PhD at Universidad del País Vasco, Spain


Excel is even today not very exact in computer intensive calculations, and Microsoft does not attend to the reported bugs quickly enough.


Doctor at Justus-Liebig-Universität Gießen, Germany


If you have a lot of data or if want to do more specialized analyses (generalized linear models, for instance), Excel is out.


Like researchers, auditors and accountants need to analyze large data sets and perform complex functions to detect trends and outliers. For this reason, many financial professionals rely on data analytics tool like IDEA for their analysis of transaction data. The tools offers:


  • The Discovery feature, which auto-generates a dashboard of visual insights into your data
  • Visualize, which allows users to build a custom dashboard
  • More than 100 common audit functions
  • Universal file conversion capabilities with read-only access to data


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About Anu Sood:

Anu Sood is the Director of Product and Corporate Marketing at CaseWare Analytics and is responsible for the company’s global marketing strategy. Prior to CaseWare Analytics, Anu worked in various roles in the high-tech industry and her accomplishments range from writing software for telephone switches to launching a new global satellite communication service. Anu has extensive experience in strategic marketing, corporate communications, demand generation, content marketing, product management, product marketing and technology development. 

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