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Thanks for the feedback! Some specific notes:

Quartiles are good; I would be curious about deciles as well. Unfortunately my primary data source, the US Bureau of Labor & Statistics, only reports 10th percentile, 25th percentile, median, 75th percentile and 90th percentile. I'm working on creating two different views: the "simple" view which just has a few relevant numbers, and the "full" view which has all the relevant data.

When I mouseover a line on the salary vs. age graph, the numbers are shown with the lowest salary on top. This is visually disconcerting as the lowest salary line is the bottom-most one on the graph.

I've gotten a few pieces of feedback on this. This is the default for how the chart generator API I'm using creates the legend. I'll have to go in and update the code on that to reverse them.

It's a bit confusing that the y-axis on the salary vs. age graph rescales to the occupation, especially since the lines are shown "rising up" from the x-axis. If I see the lines go up, it unintuitively does not mean that the salary is higher.

Do you mean like when you are looking at Job A, and then move over to look at Job B? If so, would it be more useful if the graph just consistently showed, say, $20,000 a year as the minimum and, say, $200,000 a year as the maximum, regardless of occupation? (Or any other arbitrary min/max)

There seem to be lots of duplicate categories at the "Individual Job" level, so less unique rows fit on a screen. Might be an easy way to filter these out.

This is an annoying quirk of how the BLS quantifies different positions (i.e. many positions have two separate ID codes but the same underlying data.) Version 2 will purge any redundancies like this.

I'm confused whether "entry level" means "no degree" and "post-grad" means "bachelors"

I could be more clear on this. "Entry level" means "no degree or bachelor" and "post-grad" means "masters or doctorate or equivalent".

It would be nice to have a link on the "Individual Jobs" level to the definition of each job category used by the Bureau of Labor Statistics.

This has been updated. See below for further explanation:

How many years are you taking this from? Larger n makes things more robust but makes the data less relevant to the current job market.

This currently pulls from 2014 data. Version two will have the option to pull from several years and also will include a timeline to show whether salaries for a job are trending up or down.

I'd like to know the salaries of the top and bottom deciles for each job.

The "High Salary" and "Low Salary" from the individual job breakdown is actually the 90th decile and 10th decile, respectively. I just didn't scale those according to age in the chart itself.

I don't really know why i would care about the Category ID. It seems to be an unnecessary column. It is also confusing that it starts at 11 (not 1) when I sort in descending order.

Good point. At one point I had intended to use the category ID to link to the BLS's definition of the job. But then I forgot! I have updated this. I should probably have the field itself be something more useful than the ID though.

I initially misinterpreted the "Entry Level Jobs" and "Post-Grad Jobs" as salaries

I've updated that to be more clear

I think that this emphasis on explicit, built-from-scratch mathematical proofs runs counter to your previously expressed suggestion that learning via pattern matching is more efficient than learning via explicit reasoning.

I've found that the emphasis on first principles is often symptomatic of someone who is speaking for their own benefit rather than that of their audience. After all, you're making the unwarranted assumption that A.) your audience wants first principles rather than a practical application, and B.) your audience is, for lack of a better word, too dumb to derive these principles for themselves. It's very easy to convince yourself that you are giving the audience the tools they need to understand what you're saying, when in fact, you're using the audience as a sounding board to help yourself better understand what you're actually saying.

(By the way, I'm using the "royal You" rather than specifically singling out you, Jonah. You caution against this very thing in another post of yours. ).

It's funny you mention that, that feature is actually built into the tool, it's just I hadn't written a user interface for it yet. I got your message as well, let's set up some time to talk.

The roadblock I came up against was how to return results that are useful. Many desirable-at-face-value careers (e.g. Artists, actors, etc.) have pretty high 90th percentile salaries but low average salaries. Is it useful to show people something that's possible albeit unlikely? One implementation I had toyed with was showing the number of people at that position actually making that kind of money.

Ability to compare multiple jobs simultaneously. Make a note saying the graph will appear once you pick a job, or have it pop up by default on a default job. Center the numerical figures in their cells.

One thing I was thinking about on this note was, comparing the "true cost of post-graduate education", in other words, you choose a job that will require X years of post-grad, and then you choose a job that doesn't. And it will compare lifetime earnings.

Make the list of jobs and/or the list of categories searchable and associate search keywords to jobs. For example, if I want to find 'Professor', it seems to come under postsecondary teachers, which wouldn't have been something I would have thought of without trawling the list of educators, but I would have found it if I could search by 'Professor' and get the result returned.

Good idea.

'Actuaries', 'Statisticians', 'Mathematicians' seem to have a duplicate entries. Check database for other duplicates by querying for where job names coincide.

Good catch. From looking it seems like the BLS statistics (which is what this polls from) has duplicate entries that have the same info but separate ID codes. Government efficiency right there. I'll rewrite the script to scrub these out.

Track down the figures where you don't have data, or establish that there is not enough data, and let the user know which is the case so they know the provenance of researched or omitted figures.

What specifically did you mean here?

t. Perhaps you could have a mode like the current one and a 'wandering' mode where you start with a specific job then have it compared and linked to related or similar jobs

I think the big problem with trying to determine "related jobs" is that, more often than not, in the actual job market, the relationship between similar jobs is in name only. If I'm trying to hire someone for sales, someone who has a lot of marketing experience probably isn't going to be a great candidate, even though "sales" and "marketing" seem to go hand-in-hand.

In my experience, at the under-grad level, the college you go to doesn't really matter (and especially your grades). I know that when I am hiring, I personally spend exactly 2 seconds looking at what school someone went to (and exactly 0 seconds looking at their grades).

It may be different at the post-graduate level though.

I haven't heard of them before but that looks like good stuff.

I'm thinking more at the high school level, but I think you are correct.

I think that's because, when looking at the aggregate of society, it's more efficient to bring people up to the level of semi-proficiency than it is to bring them to the level of expertise. If you have 100,000 hours of training to allocate, you get more bang for your buck to train 50 people to 80% proficiency than it is to train 10 people to the level of an expert.

The flaw, of course, is that "training hours" isn't a finite, discrete resource. Any individual can opt to spend additional time of their own accord if they are truly passionate. The problem is, at the points in our lives when we have the most free time to spend improving ourselves (read: high school), we also have the least idea of what the hell we want to do with it.

Although technically you could say that the whole argument begs the question, depending on how you interpret the logic. Because it basically follows the form: "Learning a skill is trivial because you can break a skill down into trivial subskills."

The definition of "fundamentals" differs though, depending on how abstract you get. The more layers of abstraction, the more abstract the fundamentals. If my goal is high-level programming, I don't need to know how to write code on bare metal.

That's why I advocate breaking things down until you reach the level of triviality for you personally. Most people will find, "writing a for-loop" to be trivial, without having to go farther down the rabbit hole. At a certain point, breaking things down too far actually makes things less trivial.

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