Total Access Statistics is the most advanced and popular data analysis program for Microsoft Access. Total Access Statistics makes it easy to calculate percentiles, regressions, confidence intervals, correlations, t-tests, probabilities, ANOVA, Chi-Square, etc. You can even normalize tables, rank records, and select random records, plus much more without any programming.
To maximize your use of Total Access Statistics for analyzing the data in your Microsoft Access databases, a professionally written and printed user manual is included. The user manual is 176 pages and fully indexed to make it easy to learn about Total Access Statistics, how to use it, definitions of its calculations, its programmatic interface, and tips for optimal use.
The Total Access Statistics user manual is now available for your review. Check it out to see how Total Access Statistics extends the power of Microsoft Access queries so you can analyze your data better than ever. To see it action with your own data, download the trial version.
The FMS Advanced Systems Group has a new video for its Sentinel Visualizer program: An Introduction to Social Network Analysis (SNA). If you are trying to find hidden relationships among people, places, and events, Social Network Analysis can help.
Social Network Analysis is a subset of network theory that finds important relationships and centrality in complex networks. Learn how organizations in the law enforcement, intelligence, defense, finance, and other data intensive fields are using Sentinel Visualizer in their missions.
Here’s another resource in our ongoing coverage of query techniques:
Learn how to create queries to find all the records in one table that don’t have corresponding records in another table. If you’re not familiar with the difference between Inner Join, Outer Join, Left Join and Right Join, check out our paper on Microsoft Access Outer Join Query: Finding All Records in One Table but Not Another and Creating “Not In” Queries on these important query feature. It’ll save you tons of time trying to code this yourself and will surely give you new ideas on how to better retrieve and analyze your data. The techniques apply to both Microsoft Access and SQL Server queries.
Here’s an additional paper related to our ongoing coverage of queries. This time we’re covering DELETE query syntax in Microsoft Access. In addition to the basics of deleting data and the SQL for DELETE queries, we also cover an interesting situation when DELETE queries fail during multi-table links on non-keyed fields.
If your query fails to delete any records with this message: “Could not delete from the specified tables”, learn why and how to fix it with the DISTINCTROW syntax or setting the Unique Records property to Yes.
We are all used to seeing the 'rows and columns' metaphor when looking at data. In fact it is the primary interface for many of our data analysis tasks.
But rows and columns can hide valuable patterns. What happens when you take data out of a database and visualize it as a network? Now you can see important connections, centrality, trends, movement over time, and many other key indicators.