morpheus

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

But how do you analyze your data? Is this a qualitative analysis? I'm not dissing... both data-collectors and model-builders are necessary for science to progress. It just seems that at the PhD level, you're going to have to dive into the analytical side of things, or at least use some type of analysis to guide your work (maybe in finding the ideal parts to sample, or improving the PCA mixtures, or whatever). I'm not saying you have to be an expert at solving equations, but I'm sure your undergraduate education required some kind of mathematical intuition beyond high-school math. 
The only things I'm dissing you for are (1) bragging about how bad you are at math, and (2) judging a stranger for getting rejected from a ton of programs in a field that is very much unlike your own. 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

The applicant in question was also going for a program in a hyper-competitive field: economics. I'm shocked that they let anyone into a science-related field when their practice quant score was a 4%! Were you high? 

Or it means that they applied to both reach and safety schools, and got unlucky with the safeties. Or they're switching fields and applied to many options in hopes that one would smile upon their unique background. Super judgey bro 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

Or it means that they applied to both reach and safety schools, and got unlucky with the safeties. Or they're switching fields and applied to many options in hopes that one would smile upon their unique background. Super judgey bro 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

The applicant in question was also going for a program in a hyper-competitive field: economics. I'm shocked that they let anyone into a science-related field when their practice quant score was a 4%! Were you high? 

Or it means that they applied to both reach and safety schools, and got unlucky with the safeties. Or they're switching fields and applied to many options in hopes that one would smile upon their unique background. Super judgey bro 

But how do you analyze your data? Is this a qualitative analysis? I'm not dissing... both data-collectors and model-builders are necessary for science to progress. It just seems that at the PhD level, you're going to have to dive into the analytical side of things, or at least use some type of analysis to guide your work (maybe in finding the ideal parts to sample, or improving the PCA mixtures, or whatever). I'm not saying you have to be an expert at solving equations, but I'm sure your undergraduate education required some kind of mathematical intuition beyond high-school math. 
The only things I'm dissing you for are (1) bragging about how bad you are at math, and (2) judging a stranger for getting rejected from a ton of programs in a field that is very much unlike your own. 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

Agreed! Congrats on pulling it up. It's just that a 4% is extra scary when you consider that there are plenty non-STEM majors who take the test as well. Since the GRE quant is effectively high school calculus, I would have questioned your abilities to understand basic analytical techniques in your field, e.g. carbon dating (had you not improved) 

But how do you analyze your data? Is this a qualitative analysis? I'm not dissing... both data-collectors and model-builders are necessary for science to progress. It just seems that at the PhD level, you're going to have to dive into the analytical side of things, or at least use some type of analysis to guide your work (maybe in finding the ideal parts to sample, or improving the PCA mixtures, or whatever). I'm not saying you have to be an expert at solving equations, but I'm sure your undergraduate education required some kind of mathematical intuition beyond high-school math. 
The only things I'm dissing you for are (1) bragging about how bad you are at math, and (2) judging a stranger for getting rejected from a ton of programs in a field that is very much unlike your own. 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things? 

But how do you analyze your data? Is this a qualitative analysis? I'm not dissing... both data-collectors and model-builders are necessary for science to progress. It just seems that at the PhD level, you're going to have to dive into the analytical side of things, or at least use some type of analysis to guide your work (maybe in finding the ideal parts to sample, or improving the PCA mixtures, or whatever). I'm not saying you have to be an expert at solving equations, but I'm sure your undergraduate education required some kind of mathematical intuition beyond high-school math. 
The only things I'm dissing you for are (1) bragging about how bad you are at math, and (2) judging a stranger for getting rejected from a ton of programs in a field that is very much unlike your own. 

Haha sorry, I just can't understand your research. Do you collect data and pass it off to someone else to analyze? Do you expect all your data to be fit with a nice, normal regression? How do you communicate with mathematical biologists/sociologists and computer scientists when you need fancier techniques (like machine learning, perhaps) without having a rudimentary knowledge of those things?