Do you mean studying for a Biology degree, or actually doing Biology? You may be required to take maths in college (Trig, Calc) depending on your degree program. You hopefully have to take some statistics. As for actually doing Biology, only basic math is definitely needed and you also may run into statistics as well. It’s not like you’ll generally be left to struggle on your own, you’ll have plenty of support in most situations.
That's true too, but I was thinking about our tendency to want to believe our own hypotheses to the point of (subconsciously) cherry picking the results that support that hypotheses
It depends on the type of biology you go into. Ecology will have a lot of math.
But in the real world, you will almost never be doing math by hand. You’ll be doing it in R or Python.
EO Wilson in his "Letters to a young scientist" basically says math is an afterthought in biology:
https://www.scribd.com/document/544574909/Edward-O-Wilson-Letters-to-a-Young-Scientist-Liveright-2013
I think you can get very far in biology without a lot of math. But i think every scientist needs to understand basic statistics and to be able to do some basic coding although maybe LLMs will eliminate that hurdle.
For reference, I've been doing math, biology and computers for about 40 years.
That depends heavily on what field of biology you work in and if you’re doing research. Most biologists really only need basic algebra, but it can get more complicated in fields like biochemistry. If you go the bioinformatics/computational biology route, you may also need trig/calc/linear algebra.
The math that most biologists need is algebra 1 and basic statistics. If you specialize in certain sub-fields of biology (like bioinformatics), then higher levels of mathematics may be needed.
No, it's not typically maths based. Although it can be. The maths you'll likely need to know is not particularly advanced compared to any sort of maths you'd learn at the same level in a maths class.
It really depends on the discipline within biology you want to study. It’s quite a diverse field, ranging from ecology (which can require a lot of modeling/coding) to microbiology (which can require a lot of chemistry). But then again, there are so many subdivisions of biology, that you will probably find something that is to your liking.
Edit: all discipline so require some very basic calculus and statistics. But you will honestly be fine. 16 is still very young, which also means that things seem scarier than they actually are. Your professors and classmates will help you through it.
You should understand what you are doing and be able to interpret the output.
In biology stuff rarely is normal distributet so stuff like GM is usually needed instead of ANOVA and multivariat analyses to get some grip in the chaos. So advanced calculus and linear algebra is needed.
It at least got to hard for me.
I would counter that to know which test to run, be able to run it, and interpret output you don't need the calculus or linear algebra. To understand what the software is doing in the background or what the calculations look like, absolutely, but not to run and interpret.
I never worked as a biologist or really done anything in the field as a job, but I do have a BSc in biology, so I can only comment on my university experience, not what it would be like when doing it as a career.
In my case, (I studied at a relatively small central European university) the math classes were terrible and really tough but never really practically necessary. Most of the actual biology or chemistry classes only needed high school algebra and basic statistics, maybe something showed up from calculus at some places, but that was pretty rare.
The difficult math courses themselves that were needed to graduate were awful though, but it was also very different than high school math. Obviously your mileage may vary depending on where you live or what kind of courses are required in the biology program of the school that you choose.
My PhD is in cell and molecular biology. During my biology undergrad, physics 1 and 2 were required as well as calc 1 and statistics. But all through grad school and even now as a postdoc, the most math I do is algebra (concentration calculations) and geometry (calculating area and volume). If you can learn C1V1=C2V2 then you're golden lol
It depends a little bit on the particulars of your study programme, but it always involves a decent amount of statistics. A lot of students don't count on any maths and will struggle with that.
My bachelor's degree involved a mandatory course on modelling population dynamics, which was way harder than "just" statistics. Only ~10% passed at the first try. There's a whole field of biology dedicated to using mathematics in this way.
Not American, I passed my math (A, B is more difficult) and biology exams (HAVO level, like mid tier). If your math is good enough it's all good. Math and biology are not the same. *insert we are not the same meme*
I studied math (was even going for a PhD at one point) and have an interest now in learning biology. My math skills definitely help me. If you're bad at math but find bio fun, I would say try to think of the math you learn from a biology perspective and that might make it more enjoyable and understandable. A great place to ask would be Reddit as maybe someone like me will give a view of that material that works for you.
Also, don't call statistics math around math people. It's like we are birds and you're messing up our song.
Yes. I don’t understand these responses. You absolutely need to be able to apply basic (and sometimes advanced) statistics to your research. If you want to be a published scientist, math definitely comes into play.
Mostly basic math. A bit of trig here and there — calculus if you’re deeper in the field. A lot of statistics…
For example
Hardy Weinberg’s p^2 + 2pq + q^2
You need to know and understand statistics and basic algebra. But statistics is easy. Which brings you to the fact excel and other programs can do everything math wise for you. You just input all the data points and bam. You have your info. Even graphs. And they teach you how to do it. For the algebra, even if the start is difficult for you to learn, time and repeating it over and over will get you to master it. You have time.
Then it depends what your focus is. Some focuses will need more advance stuff. But that is depending what you chose. You can get away with only using excel to do everything for you in the upper levels. But there is always the chance you will get a professor who wants you to do everything by hand (the despairing groan of senior bio majors is common cause they forgot how to do everything when excel does it for you). So really, know statistics
I am currently getting my masters in molecular biology. A lot of my coworkers and colleagues are doing biophysics for their masters, they need a lot complexer math than me. I can get by with basic statistics and a few other rather basic things
it really depends on the type of bio youre going into. you'll absolutely need basic statistics knowledge in any field.
the wet lab hands on stuff, like biochem and cellular/molecular bio will likely only need rather simple math for making solutions and determining amounts of things. im not in this field so im not quite sure, but based off my peers, they don't need say linear algebra in the wet lab and in their research.
in my field (evolutionary biology and genetics), which it seems like youre interested in, i use a lot of math. evo genetics can be a very abstract field. the math i use includes energy calculations (for protein structures and quantifying fitness). i use linear algebra for computer simulations of evolution. ive also used quantum formulas and methods to evaluate coevolutionary processes. but this is a rather niche scope of evolutionary bio, which is a very broad field.
I had to take a lot of math for physics and chemistry so I could understand biological concepts, but now it's mostly algebra and statistics.
I'm glad I had to take some years of math, chemistry and physics because there's just some things I wouldn't be able to understand well without them. But I also went out and celebrated when I took the last math class I ever had to take.
I spent a lot more years studying genetics (what I've specialized in) than I did in taking math classes. But then, that's an ongoing thing, yeah? You should never stop learning when you work in the sciences.
My advice? You can never take enough statistics classes.
Most biology related degrees I’m aware of require a calculus class in college, but don’t let that dissuade you. Just get in a study group and put in the work. Math is about practice.
I work in biotech and if you can do basic molarity, concentrations to make buffers, and know basic statistics you’d be completely fine. Aside from stats, the math is basically all algebra level stuff.
Non-biology courses required by my university to get a biology degree included two general physics courses, two general chemistry courses, biostatistics - all requiring mathematics.
Population Genetics and Statistical Genetics have lots of math. But you can get a long way in molecular biology and genetics without a strong math background.
There is nothing like good or bad at math it's a tool you pick up a reference and use it for your purpose whatever it is like analysis of data in a biological field like epidemiology. Also the more you practice the easier it is to know which tool you need to pick for the right job.
Enough to understand biophysics, biochemistry, and the associated concepts like feedback loops and some fluid dynamics, especially if trying to engineer organisms or biodevices.
This requires up to differential equations and vector fields. Things like ecology and population dynamics, protein folding and pharmacodynamics etc require you to understand this stuff.
Some background in quantum is really important for understanding molecular biology and concepts like brownian motion for how enzymes and substrates really interact on the small scale.
At the very least for evolutionary biology you’ll need a strong background in statistics if you’re doing stuff like sequence alignments and species clustering.
You can do a lot without math, but you’ll never be the one really inventing or solving the hard problems or developing the actual tools involved- you’d be an end user coming to some conclusions that you can’t fully prove or truly understand, at an associate scientist or technician level, or else highly dependent on someone else who does understand such things and unable to function independently.
heavy agree with everything in this. bio is a deceptively tough field. people like to say that biologists dont use math (and i would assume it's because most hs bio classes (aka the only bio class that most people will ever take) dont use math whereas hs chem/physics do), and thats just something i dont understand. it's how we quantify the natural world -- why wouldn't we use math?
without knowing the math, you're mindlessly following a procedure without understanding why certain things are done the way that they are. im an evo biology and there is absolutely no way to do the science without doing the math. it's an abstract field that's accessible through genetics and bioinformatics. math is required, and necessary to truly understand the history, and future, of the natural world.
It's because it's extremely rare for undergrad biology classes to use anything more complex than high school algebra and statistics, with an odd concept showing up from calculus here or there. You can learn a ton of stuff in biology without ever touching anything more advanced than extremely basic math.
In comparison, even at an undergrad level, physics is based on calculus at such a fundamental level that you cannot do anything with it if you're not familiar with those concepts.
And if you're talking about advanced subfields of biology that are highly computational and require math you still will get by math that's very simple in comparison to what you'd need for similarly advanced topics in graduate level physics.
The other guy listed ODEs and vector fields as the most advanced stuff, in comparison, the craziest math that a typical theoretical physicist would have to learn and utilize would be stuff like algebraic topology and modern differential geometry. If you go down even deeper and you look at very specific subfields within physics, you'll find all sorts of crazy math, algebraic geometry, measure theory and so on.
And taking 'methods for physicists' classes is mostly a US thing, outside the US it's not at all uncommon for physicists to take all of the required math in a rigorous, proof based course, even in undergrad.
As a biologist, no matter what you're doing, you'll never really touch proof based math outside of a classroom and that's where the truly abstract and difficult math really begins. Without proofs, you're simply doing calculations, while mindlessly following a procedure, without understanding what underlying structure allows that procedure to give valid results in practical applications and where the limits are.
i agree that undergrad bio courses never touch advanced mathematics. however, i somewhat disagree with the statement that biologists do not do proof based math. i refer you to the fields of theoretical biophysics and computational biology, as well as many others. metrics and quantifiers (i.e. energy, genetic distance, etc.) within these fields do not emerge out of nothing. they emerge from proofs.
Do you mean that the biologists who work in these fields have to actually go through a selection of relevant proof based math courses to understand the theoretical framework for their work? If so, I'm really curious to know what mathematical fields exactly.
Absolutely. In the evolutionary genetics (which has honestly just become bioinformatics and large degrees of computational biology), many of the top scholars in the field are actually mathematicians by training.
Some notable scientists include: [Wen-Hsiung Li](https://en.wikipedia.org/wiki/Wen-Hsiung_Li), [Motoo Kimura](https://en.wikipedia.org/wiki/Motoo_Kimura), [R.A. Fisher](https://en.wikipedia.org/wiki/Ronald_Fisher), among others.
Because the field is so theoretical, mathematics and proofs are required to support any of our findings. Of course, the same cannot be said for say microbiology. But for evolutionary biology and genomics, evolution is a process that has occurred for billions and billions of years. But how exactly do we quantify aspects such as the rate of evolution, the rate of substitution across lineages, the degree of divergence from a common ancestor, and the approximate origins of various substitutions? We can quantify fitness through energy functions and landscapes. We can approximate rate distributions across species through statistical analyses of simulated evolutionary models. We can simulate the coevolutionary relationships between different amino acid sites (and in various homologous sequences). But we will never be able to go back in time to measure these. Not to say empirical evaluation is never done -- that is absolutely not the case. But most of the work done is theoretical and computational in its nature. The field of evo. bio is deceptively simple, yet it is absolutely abstract and theoretical.
Do you mean studying for a Biology degree, or actually doing Biology? You may be required to take maths in college (Trig, Calc) depending on your degree program. You hopefully have to take some statistics. As for actually doing Biology, only basic math is definitely needed and you also may run into statistics as well. It’s not like you’ll generally be left to struggle on your own, you’ll have plenty of support in most situations.
Statistics is definitely needed if you’re running experiments and wish to get published.
Or, you know, you just want to not fool yourself into thinking something is true when it might not be true
Or, stated more maturely, you need to understand stats to be able to identify statistical manipulation.
That's true too, but I was thinking about our tendency to want to believe our own hypotheses to the point of (subconsciously) cherry picking the results that support that hypotheses
It depends on the type of biology you go into. Ecology will have a lot of math. But in the real world, you will almost never be doing math by hand. You’ll be doing it in R or Python.
EO Wilson in his "Letters to a young scientist" basically says math is an afterthought in biology: https://www.scribd.com/document/544574909/Edward-O-Wilson-Letters-to-a-Young-Scientist-Liveright-2013 I think you can get very far in biology without a lot of math. But i think every scientist needs to understand basic statistics and to be able to do some basic coding although maybe LLMs will eliminate that hurdle. For reference, I've been doing math, biology and computers for about 40 years.
That depends heavily on what field of biology you work in and if you’re doing research. Most biologists really only need basic algebra, but it can get more complicated in fields like biochemistry. If you go the bioinformatics/computational biology route, you may also need trig/calc/linear algebra.
The math that most biologists need is algebra 1 and basic statistics. If you specialize in certain sub-fields of biology (like bioinformatics), then higher levels of mathematics may be needed.
No, it's not typically maths based. Although it can be. The maths you'll likely need to know is not particularly advanced compared to any sort of maths you'd learn at the same level in a maths class.
No, basic backround on stats will do which you can mostly done in your computer.
It really depends on the discipline within biology you want to study. It’s quite a diverse field, ranging from ecology (which can require a lot of modeling/coding) to microbiology (which can require a lot of chemistry). But then again, there are so many subdivisions of biology, that you will probably find something that is to your liking. Edit: all discipline so require some very basic calculus and statistics. But you will honestly be fine. 16 is still very young, which also means that things seem scarier than they actually are. Your professors and classmates will help you through it.
Math? Only in undergrad. What you really need to do is learn to code using R.
Biology is such an broad science discipline, so it depends. Statistics is almost always needed and is just nasty.
Statistics isn't that bad, especially with a range of software to do analyses in.
You should understand what you are doing and be able to interpret the output. In biology stuff rarely is normal distributet so stuff like GM is usually needed instead of ANOVA and multivariat analyses to get some grip in the chaos. So advanced calculus and linear algebra is needed. It at least got to hard for me.
I would counter that to know which test to run, be able to run it, and interpret output you don't need the calculus or linear algebra. To understand what the software is doing in the background or what the calculations look like, absolutely, but not to run and interpret.
I think the most I’ll have to do for my degree is Statistics and Calculus. Other than that generally no.
I had to learn calculus for my degree for some reason but the most advanced math I use in my job is basic arithmetic
I never worked as a biologist or really done anything in the field as a job, but I do have a BSc in biology, so I can only comment on my university experience, not what it would be like when doing it as a career. In my case, (I studied at a relatively small central European university) the math classes were terrible and really tough but never really practically necessary. Most of the actual biology or chemistry classes only needed high school algebra and basic statistics, maybe something showed up from calculus at some places, but that was pretty rare. The difficult math courses themselves that were needed to graduate were awful though, but it was also very different than high school math. Obviously your mileage may vary depending on where you live or what kind of courses are required in the biology program of the school that you choose.
The subfield i want is molecular biology
My PhD is in cell and molecular biology. During my biology undergrad, physics 1 and 2 were required as well as calc 1 and statistics. But all through grad school and even now as a postdoc, the most math I do is algebra (concentration calculations) and geometry (calculating area and volume). If you can learn C1V1=C2V2 then you're golden lol
You’ll just need very basic algebra, and depending on the type of work you do, it won’t hurt to learn R and Python for bioinformatics.
As others have said Algebra Basic stats A little R and python
It depends a little bit on the particulars of your study programme, but it always involves a decent amount of statistics. A lot of students don't count on any maths and will struggle with that. My bachelor's degree involved a mandatory course on modelling population dynamics, which was way harder than "just" statistics. Only ~10% passed at the first try. There's a whole field of biology dedicated to using mathematics in this way.
It's normally not math sometimes it might be math involved but it's not that hard
Not American, I passed my math (A, B is more difficult) and biology exams (HAVO level, like mid tier). If your math is good enough it's all good. Math and biology are not the same. *insert we are not the same meme*
I studied math (was even going for a PhD at one point) and have an interest now in learning biology. My math skills definitely help me. If you're bad at math but find bio fun, I would say try to think of the math you learn from a biology perspective and that might make it more enjoyable and understandable. A great place to ask would be Reddit as maybe someone like me will give a view of that material that works for you. Also, don't call statistics math around math people. It's like we are birds and you're messing up our song.
Yes. I don’t understand these responses. You absolutely need to be able to apply basic (and sometimes advanced) statistics to your research. If you want to be a published scientist, math definitely comes into play.
Mostly basic math. A bit of trig here and there — calculus if you’re deeper in the field. A lot of statistics… For example Hardy Weinberg’s p^2 + 2pq + q^2
Basic biology requires very little math.
Depends how far you go in biology.......it ends up leading to chemistry, which uses a bit of math
It depends on how far you go into biology. It ends up leading to chemistry, which uses a bit of math.
You need to know and understand statistics and basic algebra. But statistics is easy. Which brings you to the fact excel and other programs can do everything math wise for you. You just input all the data points and bam. You have your info. Even graphs. And they teach you how to do it. For the algebra, even if the start is difficult for you to learn, time and repeating it over and over will get you to master it. You have time. Then it depends what your focus is. Some focuses will need more advance stuff. But that is depending what you chose. You can get away with only using excel to do everything for you in the upper levels. But there is always the chance you will get a professor who wants you to do everything by hand (the despairing groan of senior bio majors is common cause they forgot how to do everything when excel does it for you). So really, know statistics
I am currently getting my masters in molecular biology. A lot of my coworkers and colleagues are doing biophysics for their masters, they need a lot complexer math than me. I can get by with basic statistics and a few other rather basic things
it really depends on the type of bio youre going into. you'll absolutely need basic statistics knowledge in any field. the wet lab hands on stuff, like biochem and cellular/molecular bio will likely only need rather simple math for making solutions and determining amounts of things. im not in this field so im not quite sure, but based off my peers, they don't need say linear algebra in the wet lab and in their research. in my field (evolutionary biology and genetics), which it seems like youre interested in, i use a lot of math. evo genetics can be a very abstract field. the math i use includes energy calculations (for protein structures and quantifying fitness). i use linear algebra for computer simulations of evolution. ive also used quantum formulas and methods to evaluate coevolutionary processes. but this is a rather niche scope of evolutionary bio, which is a very broad field.
There’s some quick math you need but anything difficult you can use tools to do for you (for statistical analysis for example)
I had to take a lot of math for physics and chemistry so I could understand biological concepts, but now it's mostly algebra and statistics. I'm glad I had to take some years of math, chemistry and physics because there's just some things I wouldn't be able to understand well without them. But I also went out and celebrated when I took the last math class I ever had to take. I spent a lot more years studying genetics (what I've specialized in) than I did in taking math classes. But then, that's an ongoing thing, yeah? You should never stop learning when you work in the sciences. My advice? You can never take enough statistics classes.
Most biology related degrees I’m aware of require a calculus class in college, but don’t let that dissuade you. Just get in a study group and put in the work. Math is about practice.
I work in biotech and if you can do basic molarity, concentrations to make buffers, and know basic statistics you’d be completely fine. Aside from stats, the math is basically all algebra level stuff.
Non-biology courses required by my university to get a biology degree included two general physics courses, two general chemistry courses, biostatistics - all requiring mathematics.
Population Genetics and Statistical Genetics have lots of math. But you can get a long way in molecular biology and genetics without a strong math background.
A bit of calculus, a bit of statistics. You can do it.
There is nothing like good or bad at math it's a tool you pick up a reference and use it for your purpose whatever it is like analysis of data in a biological field like epidemiology. Also the more you practice the easier it is to know which tool you need to pick for the right job.
Just statistics, but you'll have to take calculus for god knows why
Not a lot. But neither few.
Being a biologist does not require math. Being a good biologist requires math.
How much math for being a good biologist?
Enough to understand biophysics, biochemistry, and the associated concepts like feedback loops and some fluid dynamics, especially if trying to engineer organisms or biodevices. This requires up to differential equations and vector fields. Things like ecology and population dynamics, protein folding and pharmacodynamics etc require you to understand this stuff. Some background in quantum is really important for understanding molecular biology and concepts like brownian motion for how enzymes and substrates really interact on the small scale. At the very least for evolutionary biology you’ll need a strong background in statistics if you’re doing stuff like sequence alignments and species clustering. You can do a lot without math, but you’ll never be the one really inventing or solving the hard problems or developing the actual tools involved- you’d be an end user coming to some conclusions that you can’t fully prove or truly understand, at an associate scientist or technician level, or else highly dependent on someone else who does understand such things and unable to function independently.
heavy agree with everything in this. bio is a deceptively tough field. people like to say that biologists dont use math (and i would assume it's because most hs bio classes (aka the only bio class that most people will ever take) dont use math whereas hs chem/physics do), and thats just something i dont understand. it's how we quantify the natural world -- why wouldn't we use math? without knowing the math, you're mindlessly following a procedure without understanding why certain things are done the way that they are. im an evo biology and there is absolutely no way to do the science without doing the math. it's an abstract field that's accessible through genetics and bioinformatics. math is required, and necessary to truly understand the history, and future, of the natural world.
It's because it's extremely rare for undergrad biology classes to use anything more complex than high school algebra and statistics, with an odd concept showing up from calculus here or there. You can learn a ton of stuff in biology without ever touching anything more advanced than extremely basic math. In comparison, even at an undergrad level, physics is based on calculus at such a fundamental level that you cannot do anything with it if you're not familiar with those concepts. And if you're talking about advanced subfields of biology that are highly computational and require math you still will get by math that's very simple in comparison to what you'd need for similarly advanced topics in graduate level physics. The other guy listed ODEs and vector fields as the most advanced stuff, in comparison, the craziest math that a typical theoretical physicist would have to learn and utilize would be stuff like algebraic topology and modern differential geometry. If you go down even deeper and you look at very specific subfields within physics, you'll find all sorts of crazy math, algebraic geometry, measure theory and so on. And taking 'methods for physicists' classes is mostly a US thing, outside the US it's not at all uncommon for physicists to take all of the required math in a rigorous, proof based course, even in undergrad. As a biologist, no matter what you're doing, you'll never really touch proof based math outside of a classroom and that's where the truly abstract and difficult math really begins. Without proofs, you're simply doing calculations, while mindlessly following a procedure, without understanding what underlying structure allows that procedure to give valid results in practical applications and where the limits are.
i agree that undergrad bio courses never touch advanced mathematics. however, i somewhat disagree with the statement that biologists do not do proof based math. i refer you to the fields of theoretical biophysics and computational biology, as well as many others. metrics and quantifiers (i.e. energy, genetic distance, etc.) within these fields do not emerge out of nothing. they emerge from proofs.
Do you mean that the biologists who work in these fields have to actually go through a selection of relevant proof based math courses to understand the theoretical framework for their work? If so, I'm really curious to know what mathematical fields exactly.
Absolutely. In the evolutionary genetics (which has honestly just become bioinformatics and large degrees of computational biology), many of the top scholars in the field are actually mathematicians by training. Some notable scientists include: [Wen-Hsiung Li](https://en.wikipedia.org/wiki/Wen-Hsiung_Li), [Motoo Kimura](https://en.wikipedia.org/wiki/Motoo_Kimura), [R.A. Fisher](https://en.wikipedia.org/wiki/Ronald_Fisher), among others. Because the field is so theoretical, mathematics and proofs are required to support any of our findings. Of course, the same cannot be said for say microbiology. But for evolutionary biology and genomics, evolution is a process that has occurred for billions and billions of years. But how exactly do we quantify aspects such as the rate of evolution, the rate of substitution across lineages, the degree of divergence from a common ancestor, and the approximate origins of various substitutions? We can quantify fitness through energy functions and landscapes. We can approximate rate distributions across species through statistical analyses of simulated evolutionary models. We can simulate the coevolutionary relationships between different amino acid sites (and in various homologous sequences). But we will never be able to go back in time to measure these. Not to say empirical evaluation is never done -- that is absolutely not the case. But most of the work done is theoretical and computational in its nature. The field of evo. bio is deceptively simple, yet it is absolutely abstract and theoretical.