In business schools it is common to teach statistics courses using Microsoft Excel, due to its wide accessibility and the familiarity of business students with the software. There is a large debate regarding this practice, but at this point the reality is clear: the figure that I am familiar with is about 50% of basic stat courses in b-schools use Excel and 50% use statistical software such as Minitab or JMP.

Another trend is moving from offline software to "cloud computing" -- Software such as www.statcrunch.com offer basic stat functions in an online, collaborative, social-networky style.

Following the popularity of spreadsheet software and the cloud trend, I asked myself whether the free Google Spreadsheets can actually do the job. This is part of my endeavors to find free (or at least widely accessible) software for teaching basic concepts. While Google Spreadsheets does have quite an extensive function list, I discovered that its current computing is very limited. For example, computing binomial probabilities using the function BINOMDIST is limited to a sample size of about 130 (I did report this problem). Similarly, HYPGEOMDIST results in overflow errors for reasonably small sample and population sizes.

From the old days when we used to compute binomial probabilities manually, I am guessing that whoever programmed these functions forgot to use the tricks that avoid computing high factorials in n-choose-k type calculations...

Another trend is moving from offline software to "cloud computing" -- Software such as www.statcrunch.com offer basic stat functions in an online, collaborative, social-networky style.

Following the popularity of spreadsheet software and the cloud trend, I asked myself whether the free Google Spreadsheets can actually do the job. This is part of my endeavors to find free (or at least widely accessible) software for teaching basic concepts. While Google Spreadsheets does have quite an extensive function list, I discovered that its current computing is very limited. For example, computing binomial probabilities using the function BINOMDIST is limited to a sample size of about 130 (I did report this problem). Similarly, HYPGEOMDIST results in overflow errors for reasonably small sample and population sizes.

From the old days when we used to compute binomial probabilities manually, I am guessing that whoever programmed these functions forgot to use the tricks that avoid computing high factorials in n-choose-k type calculations...