We’ve talked a lot around here about the reasons to use syntax — not only menus — in your statistical analyses.
Regardless of which software you use, the syntax file is pretty much always a text file. This is true for R, SPSS, SAS, Stata — just about all of them.
This is important because it means you can use an unlikely tool to help you code: Microsoft Word.
I know what you’re thinking. Word? Really?
Yep, it’s true. Essentially it’s because Word has much better Search-and-Replace options than your stat software’s editor.
Here are a couple features of Word’s search-and-replace that I use to help me code faster:
(more…)
Like any applied skill, mastering statistical analysis requires:
1. building a body of knowledge
2. adeptness of the tools of the trade (aka software package)
3. practice applying the knowledge and using the tools in a realistic, meaningful context.
If you think of other high-level skills you’ve mastered in your life–teaching, survey design, programming, sailing, landscaping, anything–you’ll realize the same three requirements apply.
These three requirements need to be developed over time–over many years to attain mastery. And they need to be developed together. Having more background knowledge improves understanding of how the tools work, and helps the practice go better. Likewise, practice in a real context (not perfect textbook examples) makes the knowledge make more sense, and improves skills with the tools.
I don’t know if this is true of other applied skills, but from what I’ve seen over many years of working with researchers as they master statistical analysis, the journey seems to have 3 stages. Within each stage, developing all 3 requirements–knowledge, tools, and experience–to a level of mastery sets you up well for the next stage. (more…)
