ryangreenspan wrote:yellowyak46 wrote:Well if we were to take the integral of the graph between 60 and 160k, it looks like about 30% of the salaries reported are in that range. Glad to know that you have it all figured out, though.

First off, you take integrals of functions, not of graphs. Second, there are a bunch of discrete functions between 60 and 160k, none of which we know. Third, even if we were to add up the integrals of all those functions, it would just give us a number. That number's meaningless unless we know the summation of all the integrals of all the functions in the graph.

You meant to suggest that we eyeball the area under the graph between 60 and 160k. And then compare it to the total area under the entire graph. Glad to know you're so much better at calculus than other people, though.

So uh you guys should both probably go back to Calc 1 before you start talking about integrals. You can approximate the integral under the curve and you don't need a function. You can use basic algebraic methods such as the midpoint rule or the trapezoid rule. Because I was curious and didn't want there to be any misconceptions about applying calculus or anyone's chances of salary, I went ahead and approximated the integral under the curve of the NALP graph. I used the trapezoid rule and excel. I estimated the values at each salary and I might be off. However, the NALP webpage where the graph is states: "The right-hand peak shows that salaries of $160,000 accounted for about 17% of reported salaries." So my estimates below are pretty good IMO as I am only off by 1.3 at that end. But, I still may have made a mistake somewhere or typed an equation incorrectly. NALP data I used:

http://www.nalp.org/class_of_2013_bimodal_salary_curveMy Results:

$10,000-80,000 is about a 64.8% chance

$85,000-155,000 is about a 16.9% chance

$160,000 and above is about a 18.3 % chance

Keep in mind that it was reported only 57% of all 2013 law grads had full time jobs that required job passage. Source:

http://www.americanbar.org/news/abanews ... ocia4.htmlSo the actual probabilities will be much lower when you take all 2013 law graduates into account.

My calculations: