ccwoolfolk
commented
5 years ago @WSou Here are a few questions about your compiled data. If you prefer, you can add your commentary directly to the analysis notebook (index.Rmd) and open a pull request when you are ready for feedback. I can help you do this if it is your first time (it isn't difficult once you've done it a few times but can be a little confusing at first).
- What date ranges do they represent (i.e., all within the past 12 months, 24 months, etc.)?
- What geographic region do they represent? Wichita only?
- Can 1-2 be used as examples to show how you collected the data? Ideally this would include links to the specific data points.
- Are you willing to describe your methodology in a short paragraph for documentation purposes?
- What are the strengths and weaknesses of the data set? I.e., how trustworthy should it be considered? Or, under what assumptions is it most applicable?
- How would you recommend we compare the data set to the BEA data? In particular, how should we aggregate the data representing multiple job titles and levels of experience (Junior developer vs senior developer etc. etc. etc.) into a single number that is comparable to the BLS annual salary estimate? (There is no perfect answer for this!)
This analysis makes claims regarding developer job density and salaries in Wichita. It quantifies these data in both absolute terms (developer jobs per 1000 jobs and annual salaries, respectively) and relative terms (Wichita vs Tulsa, Kansas City, etc.).
We should investigate other data sources to determine if our data are inconsistent with other sources.
Ideas:
Each comparison source should include a short description of the methodology, a link to the data set if possible, and an explanation of any relevant shortcomings (i.e., small sample size, different geographical region, etc.). We want the analysis to be fully transparent so that others can verify the results. Obviously, we will also want to summarize how the source compares to the primary BLS data set we are using.