What are YOUR exact chances? and other statistics

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sector9

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OK, I can't really tell you your EXACT chances of acceptance. Medical school admissions is much more than a game of chance. There are too many factors involved. But I can present historical acceptance data for GPA and MCAT in a more convenient way. I will use the word "chances" to describe this historical data, but keep in mind that it is not a true probability. An applicant with a bad letter of recommendation, personal statement, or interview skills might have no chance of admittance while another student with low numbers but a striking personality may be very successful. Refer to this post for additional explanation.

Instead of "My chances are x%" it is more accurate to say "Historically, x% of applicants with my GPA and MCAT were accepted."

Problem

The AAMC provides a table where you look up your percent chances in a certain bin. For example, one of the bins is for a MCAT score between 30 and 32 along with a GPA of between 3.60 and 3.79. The problem is that an applicant with a 30 on the MCAT and a GPA of 3.60 is shown as having the same chance as a student with a 32 on the MCAT and GPA of 3.79. My goal is to create a better way to look at your chances.

Important notes for using the graphs

Which GPA should you use? The GPA used in the graphs below is total undergraduate GPA. You may use this spreadsheet to calculate your GPA. Additional notes on the spreadsheet calculator can be accessed at the manual/FAQ. For official information on how your GPA is calculated, look at the following AMCAS resource. Your AMCAS GPA may be different from your school's calculation.

Which MCAT should you use? The MCAT score represented in the AAMC data is for the most recent score for each applicant. Keep in mind that each medical school may have their own policy on how they view multiple test scores.

What chances are displayed? The chances displayed in this post are chances of one or more acceptance at a U.S. allopathic (M.D.) school for all applicants. Your chances also vary depending on ethnicity/race. Those chances are displayed in subsequent posts. Also, note that these chances are only based on two data points-- cGPA and MCAT. A variety of other factors go into each admissions decision, so your chances may be higher or lower depending on the rest of your application.

On to the graphs!
The Best Estimate of Your Chances

Figure 1 (click on graph for higher resolution)

Find the colored line closest to your cumulative undergraduate GPA (cGPA) by using the legend on the right. Then find your MCAT score on the x-axis. Your chances are on the y-axis.

The solid lines correspond with the actual AAMC data. The dotted lines are merely interpolated lines drawn halfway between the solid lines.

Figure 2 (click on graph for higher resolution)

I have created a 3D graph that is not as useful for determining your chances but may be interesting to some people. The following are links to 3 different angles of the graph.

3D Graph
Figure 3 (click on link for picture)

3D Graph
Figure 4 (click on link for picture)

3D Graph
Figure 5 (click on link for picture)

Which is better: a LizzyM score composed of a high GPA/low MCAT or the same LizzyM score created from a low GPA/high MCAT?&#8232;

The available data suggests that your chances are slightly higher if your GPA contributes more to your LizzyM score.

Figure 6 (click on graph for higher resolution)

Blue dots: MCAT contributes more to your LizzyM score than the average matriculant (more than 46.6%)
Red dots: GPA contributes more to your LizzyM score than the average matriculant (more than 53.4%)

Are underrepresented in medicine (URM) applicants with less-competitive stats taking large numbers of slots from overrepresented in medicine (ORM) applicants?

No, not large numbers.

Over the past three years, an average of 18,752 students have been accepted into U.S. allopathic medical schools each year (2898 URMs accepted each year and 16,412 ORMs accepted each year. Some applicants marked multiple races or ethnicities). Only 1469 (7.8% of total accepted students) accepted students were URMs with a lower cGPA/MCAT combination than their White and Asian (ORM) counterparts.

Keep in mind that there are currently 6 medical schools that primarily accept URM students to fulfill their respective missions: Howard University College of Medicine, Meharry Medical College, Morehouse School of Medicine, Ponce School of Medicine and Health Sciences, Universidad Central del Caribe School of Medicine, and University of Puerto Rico School of Medicine. These schools combine for 513 seats per year. Not all of these 513 seats are exclusively for URMs; data available from U.S. News on three of the schools indicates minority student enrollment at 95.4%, 77.9%, and 95.2% for three of the six schools (the other three schools don't have information listed in the U.S. News database). The possible inflation of the 513 seats is mitigated by not including San Juan Bautista School of Medicine, which was accepting students through AMCAS for part of the 3 year time span represented in the Table 24 data.

After subtracting out the seats given to URMs at those 6 schools of medicine, there are approximately 956 seats (5.1% of total accepted students) given to URMs above what would be expected.

Please note that my definition of a URM applicant may be different from the definition each medical school uses. The current, official definition is found here. The definition represented by these stats is the old definition found at the same link, meaning applicants who self-identify as Black or African American, Hispanic or Latino, or American Indian or Alaskan Native (on SDN, usage of the acronym URM generally follows the old definition). In this terminology, the races overrepresented in medicine (ORM) are White and Asian.

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Methods

Sources: The main sources are "Table 24: MCAT and GPA Grid for Applicants and Acceptees to U.S. Medical Schools, 2008-2010 (aggregated)" and "Table 25: MCAT and GPA Grid for Applicants and Acceptees by Selected Race and Ethnicity, 2008-2010 (aggregated)" from the AAMC. I also used data from the 2010 MCAT examinee statistics and from "Table 17: MCAT Scores and GPAs for Applicants and Matriculants to U.S. Medical Schools, 1999-2010". All data is copyrighted by AAMC and is used for educational, noncommercial purposes.

GPA component: The GPA component is a skewed GPA based on a normal distribution of GPAs. I used the mean and standard deviation for 2010 applicants listed in Table 17 to approximate the real average for each bin. AMCAS publishes a graph in the print edition of the MSAR (the MSAR is a highly recommended resource for additional information on applications and medical schools, with ordering information available here), but they do not publish raw numbers. Based on the data published for free by AMCAS, it is impossible to fine-tune the GPA calculation any further than using the median and SD.

MCAT component: The MCAT score for each data point is also skewed. The 2010 MCAT examinee table gives the "percent achieving score" for every possible MCAT score. Since the mode of all scores is a 27 and the distribution is close to normal, the percent achieving each score gets lower as you move away from the mode. I decided to stick with the examinee statistics rather than the applicant statistics because the only data available is mean and SD, whereas the examinee stats are more detailed.

Percent Chances component: The percent chances for figures 1-6 were calculated using the data from Table 24 referenced above. The percent chances for figure 10 were calculated using Table 25.

Comment on skews: The graphs really didn't change much once I applied either the GPA or MCAT skew factors except at the limits of the data. For the 39-45 MCAT bin, the median score would be a 42. However, AAMC reports that 0.0% of all examinees scored a 43, 44, or 45. A better approximation of the bin is found using my method, yielding an average score of 39.8 for that bin.

Note on Dotted Lines in Figure 1: The dotted lines do not correspond with any of the real data from AAMC. I just added in lines that are halfway between the solid lines so that it is easier to guess your chance.

Method for Figures 3-5:
Methods are the same as above. One outlier data point was removed as well.

Method for Figure 6:
The data points are derived using the same method explained above.
For my graph, LizzyM score is defined as MCAT+cGPA*10=LizzyM
The color-coding of the graph works by comparing the LizzyM score for the data point with the "average" percent contribution of matriculants (using an average at 32 MCAT and 3.67 cGPA). The average matriculant LizzyM of 68.7 comes 46.6% from MCAT and 53.4% from GPA. I used this as the baseline percentage, so any data point where GPA contributed more than 53.4% was colored red and data where GPA contributed less was colored blue.

Method for URM statistical comparison:
My two sources for data were the three Table 25 charts "MCAT and GPA for White," "MCAT and GPA for Asian," and "MCAT and GPA for Hispanic or Latino, Black or African American, or American Indian or Alaskan Native." For each MCAT and GPA combination, I found the percentage of White and Asian applicants accepted and multiplied it by the number of URM applicants. This gave me the number of URM applicants that I would expect to be accepted if the admissions process were completely equal i.e. race and ethnicity played no role. Next, I totaled up the "expected number of accepted URMs" (I got 4503.77 for the three year period) and compared it with the actual number of URMs accepted (there were 8693 URMs accepted over the three year period). The difference between the two numbers is 4189.22 URMs accepted beyond what we would expect for that three year window.

Now that I knew how many "extra" URMs were accepted beyond what would be expected, I found out the number of available seats at the 6 medical schools listed above. The rest of the calculations are straightforward.

Here's a step-by-step look at only one of the data points (students with an MCAT between 30 and 32 and a cGPA between 3.6 and 3.79):
3811 White acceptees+1298 Asian acceptees=5109 White or Asian acceptees
5146 White applicants+1761 Asian applicants=6907 White or Asian applicants
73.97% (or 0.7397) of White or Asian applicants in this range of stats were accepted
433 URMs applied with those same stats
We would expect 433*0.7397=320.3 of the URMs to be accepted if URMs had the same acceptance percentage as White/Asian applicants
(For this data point, 379 URMs were actually accepted, or 87.5% of the URM applicants)

How well does this method work? As validation of my overall method, consider the MCAT 30-32 bin and GPA 3.6-3.79 bin for all applicants. The percent chance given by Table 24 is 72.1%. The following data points from figure 1 are included in that bin:
Code:
``````GPA  MCAT   Exact % chance
3.6   30         58%
3.6   31         64%
3.6   32         68%
3.69  30         67%
3.69  31         73%
3.69  32         76%
3.79  30         73%
3.79  31         78%
3.79  32         80%``````
[Note:I used the 3.59 GPA line for the 3.6 data]
The average % chance for the 9 points above is 70.8%, slightly below the real average from AAMC data.

Flaws in my methods include:

1. The GPA skew factor is based a normal distribution created by only mean and SD. The real data would be skewed differently if I had access to it. A graph showing GPA for actual allopathic applicants is available in the print edition of the MSAR but is unavailable due to copyright issues for my analysis.
2. Applicants to allopathic medical schools have higher MCAT scores than examinees, making my MCAT skew factor slightly off too. A graph showing MCAT scores for actual allopathic applicants is available in the print edition of the MSAR but is unavailable due to copyright issues for my analysis.
3. The dotted lines are not based on any real data, but are interpolated lines drawn in the middle of the "real" data lines.
4. It is impossible to create a line to represent a 4.0 GPA. Likewise, it is impossible to estimate chances with a MCAT score over 40.
5. Your chances also depend on your race/ethnicity, but the sample size for each data point shrinks for most of these graphs. Some counterintuitive trends can be noticed due to the small sample size.

Disclaimer:
The chances portrayed in this thread are not guaranteed by any means. I am merely presenting the best available data in a more accessible format. This thread is not meant to replace the "What Are My Chances" subforum. Every application is different, so your results will vary depending on a multitude of factors.

Previous editions from other posters:
Here are two other previous editions based on the same idea. Send me a PM if you find others!

Acknowledgements:
Big thanks to Catalystik for her advice and encouragement from the beginning of this project, apumic for advice on the statistics, mauberley for the suggestion to add a disclaimer, TriagePreMed for input on layout issues, and VC7777 for the suggestion to clarify the meaning of "your chances".

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Chances for applicants who self-identify as Hispanic or Latino

Figure 7 (click on graph for higher resolution)

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Chances for applicants who self-identify as Black or African American

Figure 8 (click on graph for higher resolution)

The chances do rise above 100% on this graph, but that's just because I prefer the smooth marked scatter graph in Excel.

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Chances for applicants who self-identify as Asian

Figure 9 (click on graph for higher resolution)

The purple solid line is being pulled down on the right due to the data point at 3.30 GPA and 39.9 MCAT. There were 32 students who applied in this bin, and only 15 were successful. Since sample size is low, it is hard to trust this point but I left it in the graph for consistency reasons.

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Chances for applicants who self-identify as White

Figure 10 (click on graph for higher resolution)

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Chances for applicants who self-identify as Hispanic or Latino, Black or African American, or American Indian or Alaskan Native (combined)

Figure 11 (click on link for picture, including outlier data point)

The data point for 3.11 GPA with a 39.8 MCAT is 0% because there was only one applicant in that bin and he or she was unsuccessful. This data point also screws up the 3.20 GPA as well (remember, dotted lines are simply drawn using data points exactly half way between the nearby lines). I made figure 12 without this outlier data point.

Figure 12 (click on graph for higher resolution)

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Very nice. i look forward to the rest. Looks like someone got bored on matlab

awesome work sector9

this should be stickied

This is awesome and should be stickied.

Did you make these plots in MATLAB?

Did you make these plots in MATLAB?
Figures 2-5 are Matlab
Figures 1 and 6 are just Excel

You just blew my mind.
In other words, nice work!

Members don't see this ad :)
What should we consider our GPA if our sGPA is lower than cGPA by 0.2? I understand the graphs are for cGPA but I heard sGPA is more important and a 0.2 GPA difference is a drastic change in percent chances

What should we consider our GPA if our sGPA is lower than cGPA by 0.2? I understand the graphs are for cGPA but I heard sGPA is more important and a 0.2 GPA difference is a drastic change in percent chances
As you've pointed out, the statistics apply only for cGPA.

I don't know that cGPA or sGPA is accepted as being more important than the other. I think that sGPA is more important than cGPA at some schools but may not be at others.

Table 17 (referenced above in the methods post) says that the average applicant has a 3.53 cGPA and a 3.43 sGPA. (Average matriculant has cGPA of 3.67 and sGPA of 3.61, so it seems like schools accept plenty of students with lower sGPA than cGPA). So the statistics published by AAMC seem to already accept a sGPA of -0.1 from cGPA. So if I were you, I would take your cGPA and subtract 0.1. This might give you a better idea of your chances, since your sGPA is 0.1 below the average difference between the two.

Sorry if this is confusing. My best guess is that you should subtract 0.1 from your cGPA and look at your chances. There isn't a better way to do it than guessing, really.

very cool, sector.

This thread is amazing, but damn you sector for making me and all the other pseudo-experts useless because all we can do now is link to this thread :-D

Look at all the purdy colors!
I kid. I'm sure I speak for everyone when I say thanks for doing the work for us! That being said, I'm pretty happy to be chillin' in the dark orange/red area

This thread is amazing. Way to represent BYU sector9

The mods need to sticky this ASAP.

Thanks for all the positive feedback, guys.

Does anyone have any requests for a race/ethnicity graph that they'd really like to see? Eventually, I'll get to all of them.

I added the graph for white applicants, btw

Thanks for all the positive feedback, guys.

Does anyone have any requests for a race/ethnicity graph that they'd really like to see? Eventually, I'll get to all of them.

I added the graph for white applicants, btw

Hispanic and African American?

Does anyone have any requests for a race/ethnicity graph that they'd really like to see? Eventually, I'll get to all of them.

URM

Me gusta

So cool. Awesome work!

Solid work!

URM

Actually ill go with the cat on this one.
OK I added the URM graph for today's contribution. (I ended up adding 2 graphs because of an outlier)

I'll work on either black or hispanic for tomorrow's project!

amazing work sector!

crazy how individual school acceptance rates are so low and your charts give me a 80-85% chance of getting accepted.

thanks sector

crazy how individual school acceptance rates are so low and your charts give me a 80-85% chance of getting accepted.

thanks sector
Technically, you gave yourself the chances. I just reported them to you

GREAT JOB!!!!! THIS IS AWESOME!!!!

Are you going to do this for every application cycle? Also, you may want to include the fact that the average applicant applies to 15 schools. Obviously applying to more would increase your chances of an acceptance.Your data also disregards the effects of a personal statement, secondary essays, LORs, and interview skills (among other things) on acceptance chances. Your graphs are very well done, but it still doesn't provide us with an "exact" percentage like you claim it does.

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OK I added the URM graph for today's contribution. (I ended up adding 2 graphs because of an outlier)

I'll work on either black or hispanic for tomorrow's project!

Great job man. I look forward to it.

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Are you going to do this for every application cycle? Also, you may want to include the fact that the average applicant applies to 15 schools. Obviously applying to more would increase your chances of an acceptance.Your data also disregards the effects of a personal statement, secondary essays, LORs, and interview skills (among other things) on acceptance chances. Your graphs are very well done, but it still doesn't provide us with an "exact" percentage.
I acknowledge your criticisms, but don't feel that they are warranted.

My goal wasn't to quantify every aspect of an application. Your letters of recommendation can only get you so far if your stats don't back it up, especially when it comes to MD admissions. I was just looking at stats.

I stated the problem I was trying to solve at the beginning of the first post. If you can come up with a way to write all of that in the title, I'm all ears. I think it is assumed that the chances presented here are rely on two data points--cGPA and MCAT.

I'll add a disclaimer to the beginning

That's why this subforum will continue to exist--just coming up with graphs doesn't give the whole picture. Knowing that UColorado is very receptive towards non-traditional applicants is very valuable information, and a non-traditional applying to medical school would be very wise to apply to that school. Does that mean that I need to state that information in my post? I don't think so.

As to your first question, I hope to make graphs for future years, but can't guarantee anything. It sounds like you don't want me to anyway

ETA: Also, one of my big reasons for making this thread is that people frequently ask about what MCAT score they need to be competitive or how much they should improve their GPA. I was trying to fill a need on SDN by creating a better way for students to assess their prospects and look at various hypothetical scenarios.

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I acknowledge your criticisms, but don't feel that they are warranted.

My goal wasn't to quantify every aspect of an application. Your letters of recommendation can only get you so far if your stats don't back it up, especially when it comes to MD admissions. I was just looking at stats.

I stated the problem I was trying to solve at the beginning of the first post. If you can come up with a way to write all of that in the title, I'm all ears. I think it is assumed that the chances presented here are rely on two data points--cGPA and MCAT.

I'll add a disclaimer to the beginning

That's why this subforum will continue to exist--just coming up with graphs doesn't give the whole picture. Knowing that UColorado is very receptive towards non-traditional applicants is very valuable information, and a non-traditional applying to medical school would be very wise to apply to that school. Does that mean that I need to state that information in my post? I don't think so.

As to your first question, I hope to make graphs for future years, but can't guarantee anything. It sounds like you don't want me to anyway

ETA: Also, one of my big reasons for making this thread is that people frequently ask about what MCAT score they need to be competitive or how much they should improve their GPA. I was trying to fill a need on SDN by creating a better way for students to assess their prospects and look at various hypothetical scenarios.

+1. great work

I acknowledge your criticisms, but don't feel that they are warranted.

My goal wasn't to quantify every aspect of an application. Your letters of recommendation can only get you so far if your stats don't back it up, especially when it comes to MD admissions. I was just looking at stats.

I stated the problem I was trying to solve at the beginning of the first post. If you can come up with a way to write all of that in the title, I'm all ears. I think it is assumed that the chances presented here are rely on two data points--cGPA and MCAT.

I'll add a disclaimer to the beginning

That's why this subforum will continue to exist--just coming up with graphs doesn't give the whole picture. Knowing that UColorado is very receptive towards non-traditional applicants is very valuable information, and a non-traditional applying to medical school would be very wise to apply to that school. Does that mean that I need to state that information in my post? I don't think so.

As to your first question, I hope to make graphs for future years, but can't guarantee anything. It sounds like you don't want me to anyway

ETA: Also, one of my big reasons for making this thread is that people frequently ask about what MCAT score they need to be competitive or how much they should improve their GPA. I was trying to fill a need on SDN by creating a better way for students to assess their prospects and look at various hypothetical scenarios.
My first post wasn't meant to be inflammatory. I appreciate the work you did putting all the data together; the graphs are very well constructed (I especially like the contour plot), and the statistical analysis is excellent.

In my previous post, I was simply saying that medical school admissions is incredibly multifaceted: there are so many factors that influence whether you get an acceptance, and it's impossible to quantify these factors effectively.

The graphs are nice, but you're not telling us anything we can't extrapolate from the AAMC data tables ourselves.

My first post wasn't meant to be inflammatory. I appreciate the work you did putting all the data together; the graphs are very well constructed (I especially like the contour plot), and the statistical analysis is excellent.

In my previous post, I was simply saying that medical school admissions is incredibly multifaceted: there are so many factors that influence whether you get an acceptance, and it's impossible to quantify these factors effectively.

The graphs are nice, but you're not telling us anything we can't extrapolate from the AAMC data tables ourselves.
I don't know why I'm wasting my time arguing with you, but you're very dense. Natural selection would eliminate you quickly.

Yes, medical school admissions is multifaceted. I never said it wasn't. I've spent plenty of time in this subforum trying to help people improve many aspects of their applications, not just their numbers. But there are clear trends in the data showing that higher numbers give people a higher chance of acceptance. It's plain and simple. So you can go ahead and bleat about "oh it's dumb to look at data when applying to medical school" or "oh I can extrapolate the data myself". Ok, why didn't you do it then?

I didn't see you posting in this thread (http://forums.studentdoctor.net/showthread.php?t=831618) complaining about how the data is all available on the individual school's websites so SDN users shouldn't make it more accessible to the casual viewer. You know why? Because you would be ripped to shreds by the general PA crowd for your dumb logic. And guess what? It is useful to look at the average stats of each school so that you can maximize your chances, and judging by the response in this thread, other users find it useful to know if they're competitive for MD admissions or not. And you'd probably rate that thread 1 star too, but who cares?

I edited my opening post already to include a disclaimer about how "numbers aren't everything."

No, I wasn't reinventing the wheel. Yes, the data is all accessible. But I didn't see you spending hours fine tuning different skews for the GPA and MCAT in each bin so that it would better represent your chances. So yes, your posts are inflammatory. If you have a problem with the statistics, I'd love to hear it. If you think certain parts could be reworded, I'd love to hear that too. But your posts explaining how worthless this all is don't add anything to the discussion. And if you didn't want to be inflammatory, you would say, "Thanks, this is useful. I like the contour plot. I think you should probably point out that numbers aren't everything though. Just my \$0.02". Your tactics are quite different than that

I don't know why I'm wasting my time arguing with you, but you're very dense. Natural selection would eliminate you quickly.

Personal insult?

Yes, medical school admissions is multifaceted. I never said it wasn't. I've spent plenty of time in this subforum trying to help people improve many aspects of their applications, not just their numbers. But there are clear trends in the data showing that higher numbers give people a higher chance of acceptance. It's plain and simple. So you can go ahead and bleat about "oh it's dumb to look at data when applying to medical school" or "oh I can extrapolate the data myself". Ok, why didn't you do it then?

I never said that. It's very important to look at data when applying to medical schools.

I didn't see you posting in this thread (http://forums.studentdoctor.net/showthread.php?t=831618) complaining about how the data is all available on the individual school's websites so SDN users shouldn't make it more accessible to the casual viewer.

That thread has a much greater breadth of original information, not just a rip-off of AAMC data tables. Plus, not every school publishes its stats.

You know why? Because you would be ripped to shreds by the general PA crowd for your dumb logic.
What dumb logic are you referring to? Or are you just slinging personal insults again?

And guess what? It is useful to look at the average stats of each school so that you can maximize your chances, and judging by the response in this thread, other users find it useful to know if they're competitive for MD admissions or not. And you'd probably rate that thread 1 star too, but who cares?

I find it useful too. That's why I was simply pointing out the fact that so much more goes into med school admissions than just GPA/MCAT.

I edited my opening post already to include a disclaimer about how "numbers aren't everything."

Thanks? I'd also include that all the information on your graphs can be found on the AAMC website.

No, I wasn't reinventing the wheel. Yes, the data is all accessible.

But I didn't see you spending hours fine tuning different skews for the GPA and MCAT in each bin so that it would better represent your chances.
You're right, I didn't spend hours making graphs using data from tables that already exist.
So yes, your posts are inflammatory. If you have a problem with the statistics, I'd love to hear it. If you think certain parts could be reworded, I'd love to hear that too.

The statistics are fine, as is the wording of the posts.

But your posts explaining how worthless this all is don't add anything to the discussion.

Did I say they are worthless? I think you're just upset that I'm not praising you like everyone else is. You took data from AAMC tables and graphed it. I'm sorry, but that isn't exactly groundbreaking.

Or maybe you're upset because I only gave your thread a one-star rating?

And if you didn't want to be inflammatory, you would say, "Thanks, this is useful. I like the contour plot. I think you should probably point out that numbers aren't everything though. Just my \$0.02". Your tactics are quite different than that

If you can't take a little criticism, how are you going to handle med school and residency?

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The statistics are fine, as is the wording of the posts.

I wrote that at 3:16 AM.

Wow... Very nice work, sector9. Thank you!

The sample size of the race/ethnicity grids does some screwy things with the graph sometimes. The graphs aren't as nice as the one in the first post, I don't think.

The sample size of the race/ethnicity grids does some screwy things with the graph sometimes. The graphs aren't as nice as the one in the first post, I don't think.

Oddly enough when you look at the AAMC chart it does have the discontinuities,

Oddly enough when you look at the AAMC chart it does have the discontinuities,
What do you mean?

What do you mean?

IIRC there were some big jumps on the AAMC charts like in the graph. And of course with single URM groups the data set will be smaller to work with to smooth it out with sample size. Small numbers just kinda show that universities, high schools, and med schools still "need" to do more to attract URM to the field

Amazing work!

IIRC there were some big jumps on the AAMC charts like in the graph. And of course with single URM groups the data set will be smaller to work with to smooth it out with sample size. Small numbers just kinda show that universities, high schools, and med schools still "need" to do more to attract URM to the field
Yup

I assume you will be doing an asian data plot, yes? By chance, is there a biracial option?

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