After a time difference mix-up on my part, I missed our weekly check-in meeting so I was unable to finish all of the tests as I had hoped to. I think, though, that I only have 2-3 more tests maximum before I can begin to summarize the data. The final tests will be comparison tests between the “control” group and our test group. Otherwise, I’ve determined that the “rate” function is best as cumulative read count \/ cumulative create count because using individual read counts is too variable.<\/p>\n
I’ve also started creating some rough charts in R to potentially use in a presentation or paper. I have an opportunity to present an update of my project at NEON (another NSF funded program) as I have been working in their offices this summer. We’ll see if they have any feedback as well on the direction we’re going and the tests that we have been using to analyze the usage data.<\/p>\n
This week I hope to finish up all of the tests after my mentor meeting tomorrow, and then re-visit my first literature review and begin to edit it to reflect what the rest of the paper will look like. I have a few sentence summaries of the tests that I may begin to fill out while we decided which tests make the most sense to include in the paper.<\/p>\n","protected":false},"excerpt":{"rendered":"
After a time difference mix-up on my part, I missed our weekly check-in meeting so I was unable to finish all of the tests as I had hoped to. I think, though, that I only have 2-3 more tests maximum before I can begin to summarize the data. The final Continue reading Week Six: Test Summaries<\/span>