A new academic year looms. This means a new crop of graduate students will begin their academic training. PDF management is a critical tool that all graduate students need to use and the sooner the better. Often these tools go hand-in-hand with a citation management system, which is also critical for graduate students.
Using a citation management software makes scholarly work easier and more effective. First and foremost, these tools allow you to automatically cite references for a paper in a wide range of bibliographic styles.
New academic year has started for most of us. I try to do a range of activities on the first day of my introductory statistics course, and one of them is an incredibly brief activity to just show students what R is and what the RStudio window looks like. Here it is:
Generate a random number between 1 and 5, and introduce yourself to that many people sitting around you:
The other day on the isostat mailing list Doug Andrews asked the following question:
Which R packages do you consider the most helpful and essential for undergrad stat ed? I ask in great part because it would help my local IT guru set up the way our network makes software available in our computer classrooms, but also just from curiosity. Doug asked for a top 10 list, and a few people have already chimed in with great suggestions.
The term “mail merge” might not be familiar to those who have not worked in an office setting, but here is the Wikipedia definition:
**Mail merge** is a software operation describing the production of multiple (and potentially large numbers of) documents from a single template form and a structured data source. The letter may be sent out to many "recipients" with small changes, such as a change of address or a change in the greeting line.
Somehow almost an entire academic year went by without a blog post, I must have been busy… It’s time to get back in the saddle! (I’m using the classical definition of this idiom here, “doing something you stopped doing for a period of time”, not the urban dictionary definition, “when you are back to doing what you do best”, as I really don’t think writing blog posts are what I do best…)
I just finished reading Willful Ignorance: The Mismeasure of Uncertainty by Herbert Weisberg. I gave this book five stars (out of five) on Goodreads.
According to Weisberg, the text can be
"regarded as two books in one. On one hand it is a history of a big idea: how we have come to _think_ about uncertainty. On the other, it is a prescription for change, especially with regard to how we perform research in the biomedical and social sciences"
John Oliver said it best: April 15 combines Americans two most-hated things: taxes and math. I’ve been thinking about the latter recently after hearing a fascinating talk last weekend about quantitative literacy.
QL is meant to describe our ability to think with, and about, numbers. QL doesn’t include high-level math skills, but usually is meant to describe our ability to understand percentages and proportions and basic mathematical operations.This is a really important type of literacy, of course, but I fear that the QL movement could benefit from merging QL with SL–Statistical Literacy.
