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1 hour ago, Miguel Sanchez said:

Can't wait to subscribe to Dr. Mullarkey's Concrete Channel

 

 

25 minutes ago, Mark Connolly said:

With the odd P&B 5s OG thrown in now and again.

I could get a guest on each week. Like that Si Ferry bloke. Some probing questions such as:

”So Lichtie, at what point did you think it was a good idea to get a Sturgeon Upskirt?”

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4 hours ago, oaksoft said:

If you are going to sneer at people, at least have the common courtesy to educate yourself.

What you've posted there in bold is completely untrue. There are many more ways to monetise a huge online audience other than through the sort of advertising you are talking about.

Those who make it (and there are many of them) don't have to worry about wasting 40 miserable years of their lives on things like morning commutes to jobs they hate and for bosses they despise, making useless crap that nobody really needs or wants, having to ask for toilet breaks or holidays. They don't have to ask for time off to watch football matches, don't have to conform to the pointless rules of others and a whole host of ridiculous nonsense most other folk have to tolerate into their 60's.

So go on. Sneer away. It's your time you are wasting. Not one of those Youtubers is going to spend a second of their lives caring one jot about what people like you think.

I certainly feel better getting that off my chest. :lol:

Just to confirm I've had QUITE a sneer..........

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3 hours ago, oaksoft said:

Anyway @Arnold Layne, to contest the many ridiculous posts on here claiming this sort of maths is "a pile of shite", I've compiled a list of practical applications for it from a book on my shelf.

The area of maths this concerns is about finding unknown things when you know part of the information and perhaps a bit of detail of restrictions or constraints. As I said before, the field is called Linear Algebra. If your son is questioning the point of this stuff this might help.

There are two parts to maths. Pure maths and applied maths. Pure mathematicians seem to be interested in discovering or inventing rules and formal relationships between things which others can then use for practical purposes if they wish. Without the pure maths guys, we'd be living in caves but it can be difficult for some kids to see why they do what they do. The other side of maths is Applied maths and it is used everywhere. Here are some examples where finding unknown things from partial information and constraints requires this type of maths. A programming language like Python would allow someone to to reasonably easily create a bit of code to demonstrate these things:-

  1. Constructing curves and surfaces and seeing where intersections between surfaces occur. Useful in things like building equations which describe shapes like lines, planes, circles, spheres and conic sections from a limited set of data points.
     
  2. Working out the centre of mass or gravity of an object. Useful for architecture, ship design,  aircraft design, anything to do with aerodynamics really.
     
  3. Working out how to balance the applied forces on an object to control its movement in certain directions. Invaluable in bridge building, anything to do with levers etc.
     
  4. Solving problems in discrete maths such as "what is the best way to travel from A to B if this route is blocked, it's rush hour and it's snowing". Used by sat navs, transportation software, logistics, search engines. It's even used in project management tools for helping to distribute personnel resources efficiently - assigning people to tasks.
     
  5. Games development. Not just 3-D manipulation of objects but also in terms of creating game algorithms themselves - games of chance, working out strategies for political parties etc. 
     
  6. Monitoring of things which change state and need to settle down such as damping of vibrations in a wind turbine, nuclear waste decay, volcano and earthquake modelling and climate/weather conditions etc.
     
  7. Artificial intelligence and machine learning where answers have to be deduced or reasoned by a computer.
     
  8. Economic modelling such as setting appropriate price structures and outputs needed to satisfy customer demand.
     
  9. Forest management where you need to optimise yield from a crop from a price perspective and also a "where do we plant" perspective. 
     
  10. Image recognition. Being able to differentiate between multiple objects on a photo for example.
     
  11. Computer graphics.
     
  12. Figuring out where electrons are likely to be sitting on chemical molecules to allow you to then predict which reactions are likely to work before you spend a fortune on the chemicals themselves. Pharmaceuticals are working on things like this as are some oil and gas companies.
     
  13. Figuring out the temperature spread in objects. Pretty important for car design, computer design, nuclear power station design etc where uneven distribution of temperature can cause dangerous hotspots.
     
  14. Monitoring propagation of genes through successive generations of living things via inheritance. Huge medical advances are promised here. Personalised medicine etc.
     
  15. Modelling population growth.
     
  16. Monitoring animal harvesting (dairy/beef farms).
     
  17. Finding errors in things such as least squares approach which can tell you about the accuracy of your results in any field.
     
  18. Solving Fourier-type problems. Important if you want to synthesise or approximate complicated wave structures to understand how things like coastal erosion can occur.
     
  19. Splining. This is where you approximate values between two data points when you don't have the real data to hand. Useful for application for blind people who want to predict where their stick should go on a curvy path. Actually a "smart walking stick" is a brilliant idea. I might look at that.
     
  20. Cryptography. Maybe your son would like to work as a spy.
     
  21. Computed tomography. This is where you take 2-D slices through 3-D objects such as with MRI machines.

I've tried to be specific. about how to use this stuff and this is just the tip of the iceberg. If your son has any interest in maths whatsoever I'm sure he'll find something on that list to make him appreciate the point of it all. 

Maths teachers in general could do a better job of showing kids these sorts of exciting applications for maths but perhaps a lot of them are Pure Maths people and might not be aware of it.

Hope this helps.

BTW the book itself is called Applications of Linear Algebra by Chris Rorres and Howard Anton. It's aimed at those who have had an introduction to Linear Algebra at the end of 1st year of uni so it's a bit advanced for your son. I add it just for reference.

I'll wait until the film comes out.

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4 hours ago, oaksoft said:

BTW the book itself is called Applications of Linear Algebra by Chris Rorres and Howard Anton. It's aimed at those who have had an introduction to Linear Algebra at the end of 1st year of uni so it's a bit advanced for your son. I add it just for reference.

It's a bit advanced for 95% of PnB.

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Anyway [mention=48810]Arnold Layne[/mention], to contest the many ridiculous posts on here claiming this sort of maths is "a pile of shite", I've compiled a list of practical applications for it from a book on my shelf.
The area of maths this concerns is about finding unknown things when you know part of the information and perhaps a bit of detail of restrictions or constraints. As I said before, the field is called Linear Algebra. If your son is questioning the point of this stuff this might help.
There are two parts to maths. Pure maths and applied maths. Pure mathematicians seem to be interested in discovering or inventing rules and formal relationships between things which others can then use for practical purposes if they wish. Without the pure maths guys, we'd be living in caves but it can be difficult for some kids to see why they do what they do. The other side of maths is Applied maths and it is used everywhere. Here are some examples where finding unknown things from partial information and constraints requires this type of maths. A programming language like Python would allow someone to to reasonably easily create a bit of code to demonstrate these things:-
  1. Constructing curves and surfaces and seeing where intersections between surfaces occur. Useful in things like building equations which describe shapes like lines, planes, circles, spheres and conic sections from a limited set of data points.
     
  2. Working out the centre of mass or gravity of an object. Useful for architecture, ship design,  aircraft design, anything to do with aerodynamics really.
     
  3. Working out how to balance the applied forces on an object to control its movement in certain directions. Invaluable in bridge building, anything to do with levers etc.
     
  4. Solving problems in discrete maths such as "what is the best way to travel from A to B if this route is blocked, it's rush hour and it's snowing". Used by sat navs, transportation software, logistics, search engines. It's even used in project management tools for helping to distribute personnel resources efficiently - assigning people to tasks.
     
  5. Games development. Not just 3-D manipulation of objects but also in terms of creating game algorithms themselves - games of chance, working out strategies for political parties etc. 
     
  6. Monitoring of things which change state and need to settle down such as damping of vibrations in a wind turbine, nuclear waste decay, volcano and earthquake modelling and climate/weather conditions etc.
     
  7. Artificial intelligence and machine learning where answers have to be deduced or reasoned by a computer.
     
  8. Economic modelling such as setting appropriate price structures and outputs needed to satisfy customer demand.
     
  9. Forest management where you need to optimise yield from a crop from a price perspective and also a "where do we plant" perspective. 
     
  10. Image recognition. Being able to differentiate between multiple objects on a photo for example.
     
  11. Computer graphics.
     
  12. Figuring out where electrons are likely to be sitting on chemical molecules to allow you to then predict which reactions are likely to work before you spend a fortune on the chemicals themselves. Pharmaceuticals are working on things like this as are some oil and gas companies.
     
  13. Figuring out the temperature spread in objects. Pretty important for car design, computer design, nuclear power station design etc where uneven distribution of temperature can cause dangerous hotspots.
     
  14. Monitoring propagation of genes through successive generations of living things via inheritance. Huge medical advances are promised here. Personalised medicine etc.
     
  15. Modelling population growth.
     
  16. Monitoring animal harvesting (dairy/beef farms).
     
  17. Finding errors in things such as least squares approach which can tell you about the accuracy of your results in any field.
     
  18. Solving Fourier-type problems. Important if you want to synthesise or approximate complicated wave structures to understand how things like coastal erosion can occur.
     
  19. Splining. This is where you approximate values between two data points when you don't have the real data to hand. Useful for application for blind people who want to predict where their stick should go on a curvy path. Actually a "smart walking stick" is a brilliant idea. I might look at that.
     
  20. Cryptography. Maybe your son would like to work as a spy.
     
  21. Computed tomography. This is where you take 2-D slices through 3-D objects such as with MRI machines.
I've tried to be specific. about how to use this stuff and this is just the tip of the iceberg. If your son has any interest in maths whatsoever I'm sure he'll find something on that list to make him appreciate the point of it all. 
Maths teachers in general could do a better job of showing kids these sorts of exciting applications for maths but perhaps a lot of them are Pure Maths people and might not be aware of it.
Hope this helps.
BTW the book itself is called Applications of Linear Algebra by Chris Rorres and Howard Anton. It's aimed at those who have had an introduction to Linear Algebra at the end of 1st year of uni so it's a bit advanced for your son. I add it just for reference.

X = 340
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4 hours ago, oaksoft said:

Anyway @Arnold Layne, to contest the many ridiculous posts on here claiming this sort of maths is "a pile of shite", I've compiled a list of practical applications for it from a book on my shelf.

The area of maths this concerns is about finding unknown things when you know part of the information and perhaps a bit of detail of restrictions or constraints. As I said before, the field is called Linear Algebra. If your son is questioning the point of this stuff this might help.

There are two parts to maths. Pure maths and applied maths. Pure mathematicians seem to be interested in discovering or inventing rules and formal relationships between things which others can then use for practical purposes if they wish. Without the pure maths guys, we'd be living in caves but it can be difficult for some kids to see why they do what they do. The other side of maths is Applied maths and it is used everywhere. Here are some examples where finding unknown things from partial information and constraints requires this type of maths. A programming language like Python would allow someone to to reasonably easily create a bit of code to demonstrate these things:-

  1. Constructing curves and surfaces and seeing where intersections between surfaces occur. Useful in things like building equations which describe shapes like lines, planes, circles, spheres and conic sections from a limited set of data points.
     
  2. Working out the centre of mass or gravity of an object. Useful for architecture, ship design,  aircraft design, anything to do with aerodynamics really.
     
  3. Working out how to balance the applied forces on an object to control its movement in certain directions. Invaluable in bridge building, anything to do with levers etc.
     
  4. Solving problems in discrete maths such as "what is the best way to travel from A to B if this route is blocked, it's rush hour and it's snowing". Used by sat navs, transportation software, logistics, search engines. It's even used in project management tools for helping to distribute personnel resources efficiently - assigning people to tasks.
     
  5. Games development. Not just 3-D manipulation of objects but also in terms of creating game algorithms themselves - games of chance, working out strategies for political parties etc. 
     
  6. Monitoring of things which change state and need to settle down such as damping of vibrations in a wind turbine, nuclear waste decay, volcano and earthquake modelling and climate/weather conditions etc.
     
  7. Artificial intelligence and machine learning where answers have to be deduced or reasoned by a computer.
     
  8. Economic modelling such as setting appropriate price structures and outputs needed to satisfy customer demand.
     
  9. Forest management where you need to optimise yield from a crop from a price perspective and also a "where do we plant" perspective. 
     
  10. Image recognition. Being able to differentiate between multiple objects on a photo for example.
     
  11. Computer graphics.
     
  12. Figuring out where electrons are likely to be sitting on chemical molecules to allow you to then predict which reactions are likely to work before you spend a fortune on the chemicals themselves. Pharmaceuticals are working on things like this as are some oil and gas companies.
     
  13. Figuring out the temperature spread in objects. Pretty important for car design, computer design, nuclear power station design etc where uneven distribution of temperature can cause dangerous hotspots.
     
  14. Monitoring propagation of genes through successive generations of living things via inheritance. Huge medical advances are promised here. Personalised medicine etc.
     
  15. Modelling population growth.
     
  16. Monitoring animal harvesting (dairy/beef farms).
     
  17. Finding errors in things such as least squares approach which can tell you about the accuracy of your results in any field.
     
  18. Solving Fourier-type problems. Important if you want to synthesise or approximate complicated wave structures to understand how things like coastal erosion can occur.
     
  19. Splining. This is where you approximate values between two data points when you don't have the real data to hand. Useful for application for blind people who want to predict where their stick should go on a curvy path. Actually a "smart walking stick" is a brilliant idea. I might look at that.
     
  20. Cryptography. Maybe your son would like to work as a spy.
     
  21. Computed tomography. This is where you take 2-D slices through 3-D objects such as with MRI machines.

I've tried to be specific. about how to use this stuff and this is just the tip of the iceberg. If your son has any interest in maths whatsoever I'm sure he'll find something on that list to make him appreciate the point of it all. 

Maths teachers in general could do a better job of showing kids these sorts of exciting applications for maths but perhaps a lot of them are Pure Maths people and might not be aware of it.

Hope this helps.

BTW the book itself is called Applications of Linear Algebra by Chris Rorres and Howard Anton. It's aimed at those who have had an introduction to Linear Algebra at the end of 1st year of uni so it's a bit advanced for your son. I add it just for reference.

Really don't need to persuade me of the benefits of maths.

 

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On 19/11/2019 at 20:47, supermik said:

Why would anybody need to do these sort of calculations in real life?

Just be speaking to my local florist.  "It's terrible - you just can't get the staff these days.  Some new flowers arrived yesterday. Tom was there to receive them but he is thick as mince.  Didn't bother to count them or anything.  All he can recall is that was four lots of white roses and one lot of red.  Not a problem, I will count them when I get the chance.  Too late, Dick added in the ones we have already got.  Fortunately I know how many that was 76 white and 48 red.  Still no problem.  Actually no.  Before I got in to work, Harry, the third idiot sent the whole lot to a customer without checking anything.  All he can remember was that there 3 times as many white roses as red.   Now I have to work out how many roses I received.  It's not easy."

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This thread has done very well from a frankly inauspicious start.

I'm reminded of the - possibly apocryphal - story about the teacher in a maths class, who was being subjected to the usual sort of complaints from one of the pupils.

"Why are you teaching us this? There's no chance I'm ever going to have to use any of it in the real world!"

"No, that's probably true; but some of the smarter children will."

There are lots of good reasons to study maths, and plenty of careers that require it; but it's not for everyone, and there are plenty of very clever people who will "get" languages and other things, but won't ever grasp maths. Similarly, some mathematicians aren't too great with the written word or other languages.

I'm making a distinction between areas in which people can be clever; not equivocating "types of intelligence", such as IQ and EQ. I'm with the great Jack Donaghy on that one:

Quote

I didn't say "stupid", Jenna!

There are many kinds of intelligence: practical, emotional... and there's actual intelligence, which is what I'm talking about.

 

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6 minutes ago, sugna said:

This thread has done very well from a frankly inauspicious start.

I'm reminded of the - possibly apocryphal - story about the teacher in a maths class, who was being subjected to the usual sort of complaints from one of the pupils.

"Why are you teaching us this? There's no chance I'm ever going to have to use any of it in the real world!"

"No, that's probably true; but some of the smarter children will."

There are lots of good reasons to study maths, and plenty of careers that require it; but it's not for everyone, and there are plenty of very clever people who will "get" languages and other things, but won't ever grasp maths. Similarly, some mathematicians aren't too great with the written word or other languages.

I'm making a distinction between areas in which people can be clever; not equivocating "types of intelligence", such as IQ and EQ. I'm with the great Jack Donaghy on that one:

 

I wasn't very good at maths and would have a recurring argument with the teacher over the wording of questions. For example, the maths books we had to work through would repeatedly pose the question "what do think the answer is?" and I'd tell her she had incorrectly marked my work as I could assure her that what I'd written down was what I was thinking. I still use my fingers for counting but did get an A for Higher English.

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