Why we have introduced linear algebra? [duplicate]
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This question already has an answer here:
Why study linear algebra?
12 answers
I am new to linear algebra and am trying to find the motivation behind defining it in such a way and need for defining it. To study $2$-D,$3$-D space we have geometry, so why do we need linear algebra then?
Why did they choose the exact properties which a vector space should have? I haven't found any satisfactory answer. The text books directly starts with the theory.
Can anyone explain please?
Edit: "Why we study linear algebra?" is different from my question. That question need the applications of linear algebra, I already know that and there are many source to answer that question. What I need is background of introduction to linear algebra, not only the history, also the motivation behind choosing the properties that need to be satisfied to be a vector space - why not extra why not less? Will taking extra or less condition give something which is not very useful? Please explain it.
linear-algebra
marked as duplicate by amWhy, uniquesolution, Shailesh, Xander Henderson, Alexander Gruber⦠Jul 29 at 5:51
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
 |Â
show 7 more comments
up vote
5
down vote
favorite
This question already has an answer here:
Why study linear algebra?
12 answers
I am new to linear algebra and am trying to find the motivation behind defining it in such a way and need for defining it. To study $2$-D,$3$-D space we have geometry, so why do we need linear algebra then?
Why did they choose the exact properties which a vector space should have? I haven't found any satisfactory answer. The text books directly starts with the theory.
Can anyone explain please?
Edit: "Why we study linear algebra?" is different from my question. That question need the applications of linear algebra, I already know that and there are many source to answer that question. What I need is background of introduction to linear algebra, not only the history, also the motivation behind choosing the properties that need to be satisfied to be a vector space - why not extra why not less? Will taking extra or less condition give something which is not very useful? Please explain it.
linear-algebra
marked as duplicate by amWhy, uniquesolution, Shailesh, Xander Henderson, Alexander Gruber⦠Jul 29 at 5:51
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
1
Linear algebra is extremely useful and has applications in math itself, as well as computing and so on. For instance, your favourite websites like Netflix rely on linear algebra (matrices and operations with them and so on).
â Dave
Jul 28 at 16:08
2
See the applications section here for some applications: en.wikipedia.org/wiki/Linear_algebra#Applications
â Dave
Jul 28 at 16:09
3
I've heard that solving linear systems of ODEs provided a lot of motivation for developing linear algebra. Also, in order to generalize the idea of the derivative to a function $f:mathbb R^n to mathbb R^m$, we need to introduce the idea of a linear transformation. The fundamental strategy of calculus is to approximate a nonlinear function locally using a linear transformation. By understanding the linear transformation, we can draw conclusions about $f$ itself. But understanding the linear transformation requires linear algebra.
â littleO
Jul 28 at 16:26
1
Anything cool you will be doing later in your education will have linear algebra in it in one way or another. The geometrical aspects of linear algebra will be maybe, I don't know... 5-10% of all aspects you will learn.
â mathreadler
Jul 28 at 17:07
3
If you want history, say so in the question itself, and say it clearly and explicitly. One should not have to read through a lot of comments to find out what distinguishes your question from the other one. You could edit further.
â David K
Jul 28 at 18:03
 |Â
show 7 more comments
up vote
5
down vote
favorite
up vote
5
down vote
favorite
This question already has an answer here:
Why study linear algebra?
12 answers
I am new to linear algebra and am trying to find the motivation behind defining it in such a way and need for defining it. To study $2$-D,$3$-D space we have geometry, so why do we need linear algebra then?
Why did they choose the exact properties which a vector space should have? I haven't found any satisfactory answer. The text books directly starts with the theory.
Can anyone explain please?
Edit: "Why we study linear algebra?" is different from my question. That question need the applications of linear algebra, I already know that and there are many source to answer that question. What I need is background of introduction to linear algebra, not only the history, also the motivation behind choosing the properties that need to be satisfied to be a vector space - why not extra why not less? Will taking extra or less condition give something which is not very useful? Please explain it.
linear-algebra
This question already has an answer here:
Why study linear algebra?
12 answers
I am new to linear algebra and am trying to find the motivation behind defining it in such a way and need for defining it. To study $2$-D,$3$-D space we have geometry, so why do we need linear algebra then?
Why did they choose the exact properties which a vector space should have? I haven't found any satisfactory answer. The text books directly starts with the theory.
Can anyone explain please?
Edit: "Why we study linear algebra?" is different from my question. That question need the applications of linear algebra, I already know that and there are many source to answer that question. What I need is background of introduction to linear algebra, not only the history, also the motivation behind choosing the properties that need to be satisfied to be a vector space - why not extra why not less? Will taking extra or less condition give something which is not very useful? Please explain it.
This question already has an answer here:
Why study linear algebra?
12 answers
linear-algebra
edited Jul 29 at 14:14
asked Jul 28 at 16:01
StanfrdMathGuy
384
384
marked as duplicate by amWhy, uniquesolution, Shailesh, Xander Henderson, Alexander Gruber⦠Jul 29 at 5:51
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
marked as duplicate by amWhy, uniquesolution, Shailesh, Xander Henderson, Alexander Gruber⦠Jul 29 at 5:51
This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.
1
Linear algebra is extremely useful and has applications in math itself, as well as computing and so on. For instance, your favourite websites like Netflix rely on linear algebra (matrices and operations with them and so on).
â Dave
Jul 28 at 16:08
2
See the applications section here for some applications: en.wikipedia.org/wiki/Linear_algebra#Applications
â Dave
Jul 28 at 16:09
3
I've heard that solving linear systems of ODEs provided a lot of motivation for developing linear algebra. Also, in order to generalize the idea of the derivative to a function $f:mathbb R^n to mathbb R^m$, we need to introduce the idea of a linear transformation. The fundamental strategy of calculus is to approximate a nonlinear function locally using a linear transformation. By understanding the linear transformation, we can draw conclusions about $f$ itself. But understanding the linear transformation requires linear algebra.
â littleO
Jul 28 at 16:26
1
Anything cool you will be doing later in your education will have linear algebra in it in one way or another. The geometrical aspects of linear algebra will be maybe, I don't know... 5-10% of all aspects you will learn.
â mathreadler
Jul 28 at 17:07
3
If you want history, say so in the question itself, and say it clearly and explicitly. One should not have to read through a lot of comments to find out what distinguishes your question from the other one. You could edit further.
â David K
Jul 28 at 18:03
 |Â
show 7 more comments
1
Linear algebra is extremely useful and has applications in math itself, as well as computing and so on. For instance, your favourite websites like Netflix rely on linear algebra (matrices and operations with them and so on).
â Dave
Jul 28 at 16:08
2
See the applications section here for some applications: en.wikipedia.org/wiki/Linear_algebra#Applications
â Dave
Jul 28 at 16:09
3
I've heard that solving linear systems of ODEs provided a lot of motivation for developing linear algebra. Also, in order to generalize the idea of the derivative to a function $f:mathbb R^n to mathbb R^m$, we need to introduce the idea of a linear transformation. The fundamental strategy of calculus is to approximate a nonlinear function locally using a linear transformation. By understanding the linear transformation, we can draw conclusions about $f$ itself. But understanding the linear transformation requires linear algebra.
â littleO
Jul 28 at 16:26
1
Anything cool you will be doing later in your education will have linear algebra in it in one way or another. The geometrical aspects of linear algebra will be maybe, I don't know... 5-10% of all aspects you will learn.
â mathreadler
Jul 28 at 17:07
3
If you want history, say so in the question itself, and say it clearly and explicitly. One should not have to read through a lot of comments to find out what distinguishes your question from the other one. You could edit further.
â David K
Jul 28 at 18:03
1
1
Linear algebra is extremely useful and has applications in math itself, as well as computing and so on. For instance, your favourite websites like Netflix rely on linear algebra (matrices and operations with them and so on).
â Dave
Jul 28 at 16:08
Linear algebra is extremely useful and has applications in math itself, as well as computing and so on. For instance, your favourite websites like Netflix rely on linear algebra (matrices and operations with them and so on).
â Dave
Jul 28 at 16:08
2
2
See the applications section here for some applications: en.wikipedia.org/wiki/Linear_algebra#Applications
â Dave
Jul 28 at 16:09
See the applications section here for some applications: en.wikipedia.org/wiki/Linear_algebra#Applications
â Dave
Jul 28 at 16:09
3
3
I've heard that solving linear systems of ODEs provided a lot of motivation for developing linear algebra. Also, in order to generalize the idea of the derivative to a function $f:mathbb R^n to mathbb R^m$, we need to introduce the idea of a linear transformation. The fundamental strategy of calculus is to approximate a nonlinear function locally using a linear transformation. By understanding the linear transformation, we can draw conclusions about $f$ itself. But understanding the linear transformation requires linear algebra.
â littleO
Jul 28 at 16:26
I've heard that solving linear systems of ODEs provided a lot of motivation for developing linear algebra. Also, in order to generalize the idea of the derivative to a function $f:mathbb R^n to mathbb R^m$, we need to introduce the idea of a linear transformation. The fundamental strategy of calculus is to approximate a nonlinear function locally using a linear transformation. By understanding the linear transformation, we can draw conclusions about $f$ itself. But understanding the linear transformation requires linear algebra.
â littleO
Jul 28 at 16:26
1
1
Anything cool you will be doing later in your education will have linear algebra in it in one way or another. The geometrical aspects of linear algebra will be maybe, I don't know... 5-10% of all aspects you will learn.
â mathreadler
Jul 28 at 17:07
Anything cool you will be doing later in your education will have linear algebra in it in one way or another. The geometrical aspects of linear algebra will be maybe, I don't know... 5-10% of all aspects you will learn.
â mathreadler
Jul 28 at 17:07
3
3
If you want history, say so in the question itself, and say it clearly and explicitly. One should not have to read through a lot of comments to find out what distinguishes your question from the other one. You could edit further.
â David K
Jul 28 at 18:03
If you want history, say so in the question itself, and say it clearly and explicitly. One should not have to read through a lot of comments to find out what distinguishes your question from the other one. You could edit further.
â David K
Jul 28 at 18:03
 |Â
show 7 more comments
3 Answers
3
active
oldest
votes
up vote
12
down vote
Textbooks about linear algebra are trying to introduce a subject which is the result of many years of deep understanding of many branches of mathematics, in the sense that linear algebra is the natural common bed for mathematical constructions that were before unrelated. A book could never cover such a huge area in an introductory chapter. A wild and bold analogy in another field could be asking: why did people invented grammar, while we already had an informal understanding of eachother?
I guess some could trace linear algebra back to the invention of infinitesimal calculus by Leibniz and Newton. When you derive a function at some point, you get the slope of the tangent of the curve at this point: this tangent line is an approximation of the function around the point. This approximation is useful because it is easy to compute. But what if I want to do the same thing for a multivariable function? Then I have partial derivatives, but they are only approximation "in one direction" taken separately. I you want an approximation of your multivariable function "in all directions at one", you need to find a way to put all of these partial approximation together. That is what formalize linear algebra, and more precisely linear maps between linear vector spaces.
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
add a comment |Â
up vote
4
down vote
In addition to other answers and comments:
linear algebra affords having a geometric intuition with things that are not naturally geometric. For instance, with linear algebra, you can deal with spaces of polynomials, of functions... and you can apply the same reasonings with polynomials, functions... in these spaces more or less as if you were dealing with vectors in $Bbb R^n$. That explains the first difficulty in linear algebra: the definition of a vector space is quite abstract at first sight. But it's precisely that abstraction which explains the great power of linear algebra (and it's often the case in maths in general) because it's that abstraction which affords applying the same language and the same theorems to so different mathematical objects.
consequently, linear algebra is part of the common language of all mathematicians. It's quite frequent to hear, at a higher level, that something "is simply linear algebra" to say that what remains to do should be easy for every mathematician listening to this conversation.
Moreover, and simpler than the other points I mentioned: we need more than 2 or 3 dimensions! Many examples:
in physics when they add time as a 4th dimension and some advanced theories like string theory use at least 10 dimensions (!) to describe reality
in functional analysis, the goal is to study spaces of functions (e.g. spaces of continuous functions on an interval, or differentiable, or integrable, or being the solutions of a particular differential equation or PDE) which can even have infinitely many dimensions!
in statistics, you may need more to study than 2 or 3 variables because in real life, a same phenomenon may depend on lot more than 2 or 3 parameters (e.g. weather can depend on temperature, wind speed, pressure, precipitations, humidity...) or you may want to compare more than 2 or 3 parameters (for instance, compare unemployment rate in 20 different countries).
1
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
add a comment |Â
up vote
3
down vote
This part from the Wikipedia article on linear algebra is nice:
- From the study of determinants and matrices to modern linear algebra
It is mostly about starting with the study of solutions of systems of linear equations and continues with the development of matrix notation up to the axiomatic definition of vector spaces.
Another line is analytic geometry, or vector geometry, combining algebra and geometry. See for example:
- Analytische Geometrie - Geschichte
Nicolas Bourbaki went a step further: he omitted geometric terms like point, line, etc. and thought with the treatment of linear algebra everything necessary was said.
Combined with calculus one arrives at vector calculus, for example, see:
- Vector calculus
One important extension going toward infinite many dimensions are:
- Hilbert spaces
An extension with linear inequalities leads to the economic important
- Linear programming
add a comment |Â
3 Answers
3
active
oldest
votes
3 Answers
3
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
12
down vote
Textbooks about linear algebra are trying to introduce a subject which is the result of many years of deep understanding of many branches of mathematics, in the sense that linear algebra is the natural common bed for mathematical constructions that were before unrelated. A book could never cover such a huge area in an introductory chapter. A wild and bold analogy in another field could be asking: why did people invented grammar, while we already had an informal understanding of eachother?
I guess some could trace linear algebra back to the invention of infinitesimal calculus by Leibniz and Newton. When you derive a function at some point, you get the slope of the tangent of the curve at this point: this tangent line is an approximation of the function around the point. This approximation is useful because it is easy to compute. But what if I want to do the same thing for a multivariable function? Then I have partial derivatives, but they are only approximation "in one direction" taken separately. I you want an approximation of your multivariable function "in all directions at one", you need to find a way to put all of these partial approximation together. That is what formalize linear algebra, and more precisely linear maps between linear vector spaces.
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
add a comment |Â
up vote
12
down vote
Textbooks about linear algebra are trying to introduce a subject which is the result of many years of deep understanding of many branches of mathematics, in the sense that linear algebra is the natural common bed for mathematical constructions that were before unrelated. A book could never cover such a huge area in an introductory chapter. A wild and bold analogy in another field could be asking: why did people invented grammar, while we already had an informal understanding of eachother?
I guess some could trace linear algebra back to the invention of infinitesimal calculus by Leibniz and Newton. When you derive a function at some point, you get the slope of the tangent of the curve at this point: this tangent line is an approximation of the function around the point. This approximation is useful because it is easy to compute. But what if I want to do the same thing for a multivariable function? Then I have partial derivatives, but they are only approximation "in one direction" taken separately. I you want an approximation of your multivariable function "in all directions at one", you need to find a way to put all of these partial approximation together. That is what formalize linear algebra, and more precisely linear maps between linear vector spaces.
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
add a comment |Â
up vote
12
down vote
up vote
12
down vote
Textbooks about linear algebra are trying to introduce a subject which is the result of many years of deep understanding of many branches of mathematics, in the sense that linear algebra is the natural common bed for mathematical constructions that were before unrelated. A book could never cover such a huge area in an introductory chapter. A wild and bold analogy in another field could be asking: why did people invented grammar, while we already had an informal understanding of eachother?
I guess some could trace linear algebra back to the invention of infinitesimal calculus by Leibniz and Newton. When you derive a function at some point, you get the slope of the tangent of the curve at this point: this tangent line is an approximation of the function around the point. This approximation is useful because it is easy to compute. But what if I want to do the same thing for a multivariable function? Then I have partial derivatives, but they are only approximation "in one direction" taken separately. I you want an approximation of your multivariable function "in all directions at one", you need to find a way to put all of these partial approximation together. That is what formalize linear algebra, and more precisely linear maps between linear vector spaces.
Textbooks about linear algebra are trying to introduce a subject which is the result of many years of deep understanding of many branches of mathematics, in the sense that linear algebra is the natural common bed for mathematical constructions that were before unrelated. A book could never cover such a huge area in an introductory chapter. A wild and bold analogy in another field could be asking: why did people invented grammar, while we already had an informal understanding of eachother?
I guess some could trace linear algebra back to the invention of infinitesimal calculus by Leibniz and Newton. When you derive a function at some point, you get the slope of the tangent of the curve at this point: this tangent line is an approximation of the function around the point. This approximation is useful because it is easy to compute. But what if I want to do the same thing for a multivariable function? Then I have partial derivatives, but they are only approximation "in one direction" taken separately. I you want an approximation of your multivariable function "in all directions at one", you need to find a way to put all of these partial approximation together. That is what formalize linear algebra, and more precisely linear maps between linear vector spaces.
answered Jul 28 at 16:45
Pece
7,92211040
7,92211040
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
add a comment |Â
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
Thank you, it partially answered my question.
â StanfrdMathGuy
Jul 29 at 14:35
add a comment |Â
up vote
4
down vote
In addition to other answers and comments:
linear algebra affords having a geometric intuition with things that are not naturally geometric. For instance, with linear algebra, you can deal with spaces of polynomials, of functions... and you can apply the same reasonings with polynomials, functions... in these spaces more or less as if you were dealing with vectors in $Bbb R^n$. That explains the first difficulty in linear algebra: the definition of a vector space is quite abstract at first sight. But it's precisely that abstraction which explains the great power of linear algebra (and it's often the case in maths in general) because it's that abstraction which affords applying the same language and the same theorems to so different mathematical objects.
consequently, linear algebra is part of the common language of all mathematicians. It's quite frequent to hear, at a higher level, that something "is simply linear algebra" to say that what remains to do should be easy for every mathematician listening to this conversation.
Moreover, and simpler than the other points I mentioned: we need more than 2 or 3 dimensions! Many examples:
in physics when they add time as a 4th dimension and some advanced theories like string theory use at least 10 dimensions (!) to describe reality
in functional analysis, the goal is to study spaces of functions (e.g. spaces of continuous functions on an interval, or differentiable, or integrable, or being the solutions of a particular differential equation or PDE) which can even have infinitely many dimensions!
in statistics, you may need more to study than 2 or 3 variables because in real life, a same phenomenon may depend on lot more than 2 or 3 parameters (e.g. weather can depend on temperature, wind speed, pressure, precipitations, humidity...) or you may want to compare more than 2 or 3 parameters (for instance, compare unemployment rate in 20 different countries).
1
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
add a comment |Â
up vote
4
down vote
In addition to other answers and comments:
linear algebra affords having a geometric intuition with things that are not naturally geometric. For instance, with linear algebra, you can deal with spaces of polynomials, of functions... and you can apply the same reasonings with polynomials, functions... in these spaces more or less as if you were dealing with vectors in $Bbb R^n$. That explains the first difficulty in linear algebra: the definition of a vector space is quite abstract at first sight. But it's precisely that abstraction which explains the great power of linear algebra (and it's often the case in maths in general) because it's that abstraction which affords applying the same language and the same theorems to so different mathematical objects.
consequently, linear algebra is part of the common language of all mathematicians. It's quite frequent to hear, at a higher level, that something "is simply linear algebra" to say that what remains to do should be easy for every mathematician listening to this conversation.
Moreover, and simpler than the other points I mentioned: we need more than 2 or 3 dimensions! Many examples:
in physics when they add time as a 4th dimension and some advanced theories like string theory use at least 10 dimensions (!) to describe reality
in functional analysis, the goal is to study spaces of functions (e.g. spaces of continuous functions on an interval, or differentiable, or integrable, or being the solutions of a particular differential equation or PDE) which can even have infinitely many dimensions!
in statistics, you may need more to study than 2 or 3 variables because in real life, a same phenomenon may depend on lot more than 2 or 3 parameters (e.g. weather can depend on temperature, wind speed, pressure, precipitations, humidity...) or you may want to compare more than 2 or 3 parameters (for instance, compare unemployment rate in 20 different countries).
1
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
add a comment |Â
up vote
4
down vote
up vote
4
down vote
In addition to other answers and comments:
linear algebra affords having a geometric intuition with things that are not naturally geometric. For instance, with linear algebra, you can deal with spaces of polynomials, of functions... and you can apply the same reasonings with polynomials, functions... in these spaces more or less as if you were dealing with vectors in $Bbb R^n$. That explains the first difficulty in linear algebra: the definition of a vector space is quite abstract at first sight. But it's precisely that abstraction which explains the great power of linear algebra (and it's often the case in maths in general) because it's that abstraction which affords applying the same language and the same theorems to so different mathematical objects.
consequently, linear algebra is part of the common language of all mathematicians. It's quite frequent to hear, at a higher level, that something "is simply linear algebra" to say that what remains to do should be easy for every mathematician listening to this conversation.
Moreover, and simpler than the other points I mentioned: we need more than 2 or 3 dimensions! Many examples:
in physics when they add time as a 4th dimension and some advanced theories like string theory use at least 10 dimensions (!) to describe reality
in functional analysis, the goal is to study spaces of functions (e.g. spaces of continuous functions on an interval, or differentiable, or integrable, or being the solutions of a particular differential equation or PDE) which can even have infinitely many dimensions!
in statistics, you may need more to study than 2 or 3 variables because in real life, a same phenomenon may depend on lot more than 2 or 3 parameters (e.g. weather can depend on temperature, wind speed, pressure, precipitations, humidity...) or you may want to compare more than 2 or 3 parameters (for instance, compare unemployment rate in 20 different countries).
In addition to other answers and comments:
linear algebra affords having a geometric intuition with things that are not naturally geometric. For instance, with linear algebra, you can deal with spaces of polynomials, of functions... and you can apply the same reasonings with polynomials, functions... in these spaces more or less as if you were dealing with vectors in $Bbb R^n$. That explains the first difficulty in linear algebra: the definition of a vector space is quite abstract at first sight. But it's precisely that abstraction which explains the great power of linear algebra (and it's often the case in maths in general) because it's that abstraction which affords applying the same language and the same theorems to so different mathematical objects.
consequently, linear algebra is part of the common language of all mathematicians. It's quite frequent to hear, at a higher level, that something "is simply linear algebra" to say that what remains to do should be easy for every mathematician listening to this conversation.
Moreover, and simpler than the other points I mentioned: we need more than 2 or 3 dimensions! Many examples:
in physics when they add time as a 4th dimension and some advanced theories like string theory use at least 10 dimensions (!) to describe reality
in functional analysis, the goal is to study spaces of functions (e.g. spaces of continuous functions on an interval, or differentiable, or integrable, or being the solutions of a particular differential equation or PDE) which can even have infinitely many dimensions!
in statistics, you may need more to study than 2 or 3 variables because in real life, a same phenomenon may depend on lot more than 2 or 3 parameters (e.g. weather can depend on temperature, wind speed, pressure, precipitations, humidity...) or you may want to compare more than 2 or 3 parameters (for instance, compare unemployment rate in 20 different countries).
answered Jul 28 at 17:11
paf
3,9511823
3,9511823
1
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
add a comment |Â
1
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
1
1
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Also it might be worth mentioning that in physics, such as in classical mechanics, the number of parameters required to describe the state of a system (such as a coupled pendulum system) is often more than 3. So in this situation also we find ourselves working with $n$-tuples where $n$ is large.
â littleO
Jul 28 at 19:35
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
Excellent answer, I would add that your example about functional analysis applies to physics because Hilbert spaces are fundamental for quantum theory.
â Eben Cowley
Jul 29 at 3:23
add a comment |Â
up vote
3
down vote
This part from the Wikipedia article on linear algebra is nice:
- From the study of determinants and matrices to modern linear algebra
It is mostly about starting with the study of solutions of systems of linear equations and continues with the development of matrix notation up to the axiomatic definition of vector spaces.
Another line is analytic geometry, or vector geometry, combining algebra and geometry. See for example:
- Analytische Geometrie - Geschichte
Nicolas Bourbaki went a step further: he omitted geometric terms like point, line, etc. and thought with the treatment of linear algebra everything necessary was said.
Combined with calculus one arrives at vector calculus, for example, see:
- Vector calculus
One important extension going toward infinite many dimensions are:
- Hilbert spaces
An extension with linear inequalities leads to the economic important
- Linear programming
add a comment |Â
up vote
3
down vote
This part from the Wikipedia article on linear algebra is nice:
- From the study of determinants and matrices to modern linear algebra
It is mostly about starting with the study of solutions of systems of linear equations and continues with the development of matrix notation up to the axiomatic definition of vector spaces.
Another line is analytic geometry, or vector geometry, combining algebra and geometry. See for example:
- Analytische Geometrie - Geschichte
Nicolas Bourbaki went a step further: he omitted geometric terms like point, line, etc. and thought with the treatment of linear algebra everything necessary was said.
Combined with calculus one arrives at vector calculus, for example, see:
- Vector calculus
One important extension going toward infinite many dimensions are:
- Hilbert spaces
An extension with linear inequalities leads to the economic important
- Linear programming
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This part from the Wikipedia article on linear algebra is nice:
- From the study of determinants and matrices to modern linear algebra
It is mostly about starting with the study of solutions of systems of linear equations and continues with the development of matrix notation up to the axiomatic definition of vector spaces.
Another line is analytic geometry, or vector geometry, combining algebra and geometry. See for example:
- Analytische Geometrie - Geschichte
Nicolas Bourbaki went a step further: he omitted geometric terms like point, line, etc. and thought with the treatment of linear algebra everything necessary was said.
Combined with calculus one arrives at vector calculus, for example, see:
- Vector calculus
One important extension going toward infinite many dimensions are:
- Hilbert spaces
An extension with linear inequalities leads to the economic important
- Linear programming
This part from the Wikipedia article on linear algebra is nice:
- From the study of determinants and matrices to modern linear algebra
It is mostly about starting with the study of solutions of systems of linear equations and continues with the development of matrix notation up to the axiomatic definition of vector spaces.
Another line is analytic geometry, or vector geometry, combining algebra and geometry. See for example:
- Analytische Geometrie - Geschichte
Nicolas Bourbaki went a step further: he omitted geometric terms like point, line, etc. and thought with the treatment of linear algebra everything necessary was said.
Combined with calculus one arrives at vector calculus, for example, see:
- Vector calculus
One important extension going toward infinite many dimensions are:
- Hilbert spaces
An extension with linear inequalities leads to the economic important
- Linear programming
edited Jul 28 at 18:46
Peter Mortensen
530310
530310
answered Jul 28 at 16:27
mvw
30.2k22250
30.2k22250
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1
Linear algebra is extremely useful and has applications in math itself, as well as computing and so on. For instance, your favourite websites like Netflix rely on linear algebra (matrices and operations with them and so on).
â Dave
Jul 28 at 16:08
2
See the applications section here for some applications: en.wikipedia.org/wiki/Linear_algebra#Applications
â Dave
Jul 28 at 16:09
3
I've heard that solving linear systems of ODEs provided a lot of motivation for developing linear algebra. Also, in order to generalize the idea of the derivative to a function $f:mathbb R^n to mathbb R^m$, we need to introduce the idea of a linear transformation. The fundamental strategy of calculus is to approximate a nonlinear function locally using a linear transformation. By understanding the linear transformation, we can draw conclusions about $f$ itself. But understanding the linear transformation requires linear algebra.
â littleO
Jul 28 at 16:26
1
Anything cool you will be doing later in your education will have linear algebra in it in one way or another. The geometrical aspects of linear algebra will be maybe, I don't know... 5-10% of all aspects you will learn.
â mathreadler
Jul 28 at 17:07
3
If you want history, say so in the question itself, and say it clearly and explicitly. One should not have to read through a lot of comments to find out what distinguishes your question from the other one. You could edit further.
â David K
Jul 28 at 18:03