Chapter 5 Summarize

The summarize feature is designed to be more of a quick summary feature that provides an quick look at the summary statistics of your project with minimal user-implemented choices. I found it to be convenient when you just want a quick check on how a project is progressing wanting to see averages, standard errors, sample size, etc to update myself and the lab. You can change colors or re-reorder the factors for display purposes, but other than that it will create the same default statistical figures powered by the {ggstatsplot} package. This provides a quick statistical tasks to check on significance. Currently, conditions are grouped indivudally and performed in a “one-way” fashion. Click the link to visit the {ggstatsplot} website for insight into the meanings of all the statistical symbols. These quick summaries can be exported to standalone .html dashboards to share. In the future I would like to add support to export to .ppt files as well.

Summarizing data will read, filter, combine, and save all “measured-events.csv” into your “summary” folder within your project with the date, project name, and “all-measured-events.csv” as the identifying file name. The summarized data will also be saved in a similar fashion but as “summary-data.csv”.

Note: The split conditions feature can be used to separate your conditions name into multiple unique variable ID’s which can be useful for later use when creating plots. Split conditions only works if you follow the condition naming convention described in these docs. No spaces - EVER! Underscores “_” separate distinct varaibles and dashes “-” can be used as spaces within a variable. When selecting split conditions, n number of textboxes will appear for the number of variables present in your conditions name, which is solved by identifying the number of underscores present plus 1. You can then enter the variables names which will become column names in the data.

5.1 tl;dr

Just show me a video…