5 ms·

This is a question I've been meaning to ask on here, but didn't think it warranted its own "Ask HN": What's the best way for someone with an otherwise decent ma

by defen 17y ago

This is a question I've been meaning to ask on here, but didn't think it warranted its own "Ask HN": What's the best way for someone with an otherwise decent math background, but no statistics, to get started on the topic? Any particular books, websites, etc that people recommend?

crsmith 17y ago
There was an Ask Metafilter question about learning stats. http://ask.metafilter.com/105045/Best-way-to-relearn-statistics http://ask.metafilter.com/105045/Best-way-to-relearn-statist...
- swaroop 17y ago
  Have you checked out Head First Statistics by O'Reilly?
aquateen 17y ago
This was a good read: http://www.zedshaw.com/essays/programmer_stats.html http://www.zedshaw.com/essays/programmer_stats.html He even mentioned just about every topic we covered in my stats/probability class. There's a book list at the end.
dkersten 17y ago
I recently got this book: http://www.amazon.com/Statistics-Gentle-Introduction-Frederick-Coolidge/dp/1412924944 http://www.amazon.com/Statistics-Gentle-Introduction-Frederi... I found it to be perfect for what I wanted. Basically, my knowledge of statistics was VERY limited, but one of the things I'm working on now requires a good understanding, so.. The book is gentle and not too math heavy. Everything it covers, it does so in detail and with examples and real-world stories. I found it to be a good way to get a basic foundation. You may want to follow up with a more advanced book after though.
tezza 17y ago
I got an excellent introduction to Statistics in my Computer Engineering degree[1][2]. It is for the practical day-to-day use of stats. Applied Statistics for Engineers and Scientists , 2nd Edition, J. Devore and N. Farnum, Duxbury Press, Thomson Publishers[3] Hope this helps. ----------- [1] http://www.maths.unsw.edu.au/students/current/homepages/math2859s2.html#CourseOverview http://www.maths.unsw.edu.au/students/current/homepages/math... [2] Set text and course overview :: http://www.maths.unsw.edu.au/students/current/homepages/outlines/math2859s2.pdf http://www.maths.unsw.edu.au/students/current/homepages/outl... [3] http://www.amazon.com/Applied-Statistics-Engineers-Scientists-CD-ROM/dp/0534467199/ref=sr_1_1?ie=UTF8&s=books&qid=1249555586&sr=1-1 http://www.amazon.com/Applied-Statistics-Engineers-Scientist...
- tokenadult 17y ago
  Devore is a very good author on statistics.
dantheman 17y ago
I can't recommend Cartoon Guide to Statistics by Larry Gonick and Woollcott Smith enough. It's a great resource for developing an intuitive understanding and can often answer questions by explaining the concepts in a different way that traditional texts. http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025/ref=sr_1_1?ie=UTF8&qid=1249555652&sr=8-1 http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/...
fauigerzigerk 17y ago
I found Sheldon Ross, Introductory Statistics very approachable http://www.amazon.com/Introductory-Statistics-Second-Sheldon-Ross/dp/012597132X/ref=sr_1_1?ie=UTF8&s=books&qid=1249558315&sr=1-1 http://www.amazon.com/Introductory-Statistics-Second-Sheldon...
rdouble 17y ago
I was in the same boat as you. I have an undergrad math degree but took no statistics. I have found that most statistics books are inscrutable at best and complete wastes of paper and effort at worst. Based on the book recommendations I've been given by people who supposedly use statistics all the time, I don't believe that many trained statisticians have any idea what they are doing. That said, here's what has sort of worked for me: - Cartoon Guide to Statistics by Larry Gonick - Fundamentals of Applied Probability Theory by Al Drake: out of print, and mostly about probability. However, the stats intro at the end is the clearest one I've ever read. Originally recommended to me by Philip Greenspun. - Introductory Statistics with R by Peter Dalgaard. I'm assuming if you are posting to Hacker News you probably are coming from a programming background. This book does exactly what the title says, shows you how to apply introductory statistics by programming. It's heavier on R than stats.
- tokenadult 17y ago
  Based on the book recommendations I've been given by people who supposedly use statistics all the time, I don't believe that many trained statisticians have any idea what they are doing. Many people working with statistics in their employment have never grappled with the issues of adequate descriptive statistics or reasonable inference. Besides the recommendations I just posted above, http://statland.org/MyPapers/MAAFIXED.PDF http://statland.org/MyPapers/MAAFIXED.PDF http://repositories.cdlib.org/cgi/viewcontent.cgi?article=1002&context=uclastat/cts/tise http://repositories.cdlib.org/cgi/viewcontent.cgi?article=10... see Statistics: A Guide to the Unknown 4th edition http://www.amazon.com/Statistics-Guide-Roxy-Peck/dp/0534372821 http://www.amazon.com/Statistics-Guide-Roxy-Peck/dp/05343728... for articles with examples of what statistics is really all about.
- arakyd 17y ago
  Second the idea that a lot of statisticians don't know what they're doing. The first mistake is to make things easier by glossing over, or mangling, the mathematical details. Many statistics textbooks do this, and the only real protection is to have a good math background. The second mistake is to treat statistics like a bunch of techniques to be learned and applied with little regard for the philosophical problems inherent in every attempt to model the real world. The Cartoon Guide to Statistics is an excellent way to go from zero to a good overview of the basics with a minimum of hard math. After that, if you're mostly interested in applying basic techniques to your own stuff, you want a good undergrad textbook. I don't have any good recommendations here, unfortunately. If you have a good math background (or are motivated to get it) and you want to keep going, Statistical Models; Theory and Practice by David A. Freedman (http://www.amazon.com/review/R2XUNM92KYU7BB http://www.amazon.com/review/R2XUNM92KYU7BB) has the math, the philosophy, the hands on analysis of studies, and the exercises to put you in a better position to evaluate statistical research than some people who produce it.
physcab 17y ago
The key is to come up with a well-formulated question, such as "I wonder if I can predict stock trends." Then in doing so, you'll search the web and come across predictive modeling, which will lead to machine learning techniques, which will lead to good resources. Within those machine learning sources, search for chapters on prediction and classification, and you'll come across regression techniques, support vector machines, relevance vector machines, etc. Then you'll wonder, "ok, how do I actually solve this problem" so you may search for "SVM implementations" and find Steve Gunn's for Matlab for example. Then after much codebanging, you'll realize that inorder to solve this problem, you need a good dataset, so you go to Yahoo finance and see if you can download some data for IBM. This is usually the process one needs to follow, albeit with some intermediate steps switched out for others here and there.
- discojesus 17y ago
  it seems like if he did that, he'd be biting off WAY more than he can chew at the present time. If you want to learn statistics, it's probably better to start at the beginning (_Cartoon Guide to Statistics_, O'Reilly's new _Head First Statistics_, or Huff's _How to Lie With Statistics_) than to leap headlong into a huge, mostly intractable problem and pagefault in knowledge at each point you come across something you don't know how to do.
  - physcab 17y ago
    I agree, but at the same time, you only learn by doing. In my experience, even when you dive in way over your head, you tend to pick up the information rather quickly. I took a machine learning class with no statistics background and after a few weeks of floundering and learning terminology I was fine. The benefit of forming a problem first gives you an ultimate goal of which to work towards. Don't tell Google that it's slogan ("Organize the world's information") is biting off more than it could chew.
    - timwiseman 17y ago
      I agree with you, starting with a problem can help provide motivation, structure, and focus and all of those can help keep you learning quickly. Still, there is a place for an introductory book if you are truly coming from minimal knowledge of the subject.
tokenadult 17y ago
My two favorite orientations to what statistics is all about are two free articles on the Web. Both recommend books for further reading, and they are good books. "Advice to Mathematics Teachers on Evaluating Introductory Statistics Textbooks" http://statland.org/MyPapers/MAAFIXED.PDF http://statland.org/MyPapers/MAAFIXED.PDF "The Introductory Statistics Course: A Ptolemaic Curriculum?" http://repositories.cdlib.org/cgi/viewcontent.cgi?article=1002&context=uclastat/cts/tise http://repositories.cdlib.org/cgi/viewcontent.cgi?article=10... Here's a list of the best beginning textbooks: http://www.mrderksen.com/textbooks.htm http://www.mrderksen.com/textbooks.htm
timwiseman 17y ago
It is only a brief introduction and should be nothing more than a starting point, but "The Manga Guide To Statistics" http://www.amazon.com/Manga-Guide-Statistics-Shin-Takahashi/dp/1593271891/ref=sr_1_1?ie=UTF8&qid=1249566654&sr=8-1 http://www.amazon.com/Manga-Guide-Statistics-Shin-Takahashi/... is a good first book.
tel 17y ago
Physcab suggests a great step #2: diving into some real statistics problems. The information available online today is more than at that point. Step #1 is going to be getting the foundations so that you can quickly digest the meaning and purpose of things like machine learning. Fortunately, statistics can be largely summarized as "the science/math/art of explaining variance". Study what variance is and means and you'll dive through probability, distributions, modeling, inference, prediction, parametrization, simulation, and all of those fun topics while keeping an understanding for why they exist. Finally, I'd highly suggest taking a look at Tufte's work because once you understand variance, you've still got to explain it.
bravura 17y ago
Get the machine learning book by Bishop.
stanleydrew 17y ago
I highly recommend Hayashi's book on Econometrics. It's what we used in the first year of my PhD program in Economics. But it's probably worth starting with a basic probability and statistics book, preferably one that's pretty mathematical. I've used Hogg McKean and Craig's Introduction to Mathematical Statistics and it's really good.
mbrubeck 17y ago
O'Reilly's Statistics In a Nutshell is quite good as both a textbook and a reference. I'm (slowly) working through it on my own.

by defen 17y ago

crsmith 17y ago

There was an Ask Metafilter question about learning stats. http://ask.metafilter.com/105045/Best-way-to-relearn-statistics http://ask.metafilter.com/105045/Best-way-to-relearn-statist...

swaroop 17y ago
Have you checked out Head First Statistics by O'Reilly?

aquateen 17y ago

This was a good read: http://www.zedshaw.com/essays/programmer_stats.html http://www.zedshaw.com/essays/programmer_stats.html He even mentioned just about every topic we covered in my stats/probability class. There's a book list at the end.

dkersten 17y ago

I recently got this book: http://www.amazon.com/Statistics-Gentle-Introduction-Frederick-Coolidge/dp/1412924944 http://www.amazon.com/Statistics-Gentle-Introduction-Frederi... I found it to be perfect for what I wanted. Basically, my knowledge of statistics was VERY limited, but one of the things I'm working on now requires a good understanding, so.. The book is gentle and not too math heavy. Everything it covers, it does so in detail and with examples and real-world stories. I found it to be a good way to get a basic foundation. You may want to follow up with a more advanced book after though.

tezza 17y ago

I got an excellent introduction to Statistics in my Computer Engineering degree[1][2]. It is for the practical day-to-day use of stats. Applied Statistics for Engineers and Scientists , 2nd Edition, J. Devore and N. Farnum, Duxbury Press, Thomson Publishers[3] Hope this helps. ----------- [1] http://www.maths.unsw.edu.au/students/current/homepages/math2859s2.html#CourseOverview http://www.maths.unsw.edu.au/students/current/homepages/math... [2] Set text and course overview :: http://www.maths.unsw.edu.au/students/current/homepages/outlines/math2859s2.pdf http://www.maths.unsw.edu.au/students/current/homepages/outl... [3] http://www.amazon.com/Applied-Statistics-Engineers-Scientists-CD-ROM/dp/0534467199/ref=sr_1_1?ie=UTF8&s=books&qid=1249555586&sr=1-1 http://www.amazon.com/Applied-Statistics-Engineers-Scientist...

tokenadult 17y ago
Devore is a very good author on statistics.

dantheman 17y ago

I can't recommend Cartoon Guide to Statistics by Larry Gonick and Woollcott Smith enough. It's a great resource for developing an intuitive understanding and can often answer questions by explaining the concepts in a different way that traditional texts. http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/dp/0062731025/ref=sr_1_1?ie=UTF8&qid=1249555652&sr=8-1 http://www.amazon.com/Cartoon-Guide-Statistics-Larry-Gonick/...

fauigerzigerk 17y ago

I found Sheldon Ross, Introductory Statistics very approachable http://www.amazon.com/Introductory-Statistics-Second-Sheldon-Ross/dp/012597132X/ref=sr_1_1?ie=UTF8&s=books&qid=1249558315&sr=1-1 http://www.amazon.com/Introductory-Statistics-Second-Sheldon...

rdouble 17y ago

I was in the same boat as you. I have an undergrad math degree but took no statistics. I have found that most statistics books are inscrutable at best and complete wastes of paper and effort at worst. Based on the book recommendations I've been given by people who supposedly use statistics all the time, I don't believe that many trained statisticians have any idea what they are doing. That said, here's what has sort of worked for me: - Cartoon Guide to Statistics by Larry Gonick - Fundamentals of Applied Probability Theory by Al Drake: out of print, and mostly about probability. However, the stats intro at the end is the clearest one I've ever read. Originally recommended to me by Philip Greenspun. - Introductory Statistics with R by Peter Dalgaard. I'm assuming if you are posting to Hacker News you probably are coming from a programming background. This book does exactly what the title says, shows you how to apply introductory statistics by programming. It's heavier on R than stats.

tokenadult 17y ago
Based on the book recommendations I've been given by people who supposedly use statistics all the time, I don't believe that many trained statisticians have any idea what they are doing. Many people working with statistics in their employment have never grappled with the issues of adequate descriptive statistics or reasonable inference. Besides the recommendations I just posted above, http://statland.org/MyPapers/MAAFIXED.PDF http://statland.org/MyPapers/MAAFIXED.PDF http://repositories.cdlib.org/cgi/viewcontent.cgi?article=1002&context=uclastat/cts/tise http://repositories.cdlib.org/cgi/viewcontent.cgi?article=10... see Statistics: A Guide to the Unknown 4th edition http://www.amazon.com/Statistics-Guide-Roxy-Peck/dp/0534372821 http://www.amazon.com/Statistics-Guide-Roxy-Peck/dp/05343728... for articles with examples of what statistics is really all about.
arakyd 17y ago
Second the idea that a lot of statisticians don't know what they're doing. The first mistake is to make things easier by glossing over, or mangling, the mathematical details. Many statistics textbooks do this, and the only real protection is to have a good math background. The second mistake is to treat statistics like a bunch of techniques to be learned and applied with little regard for the philosophical problems inherent in every attempt to model the real world. The Cartoon Guide to Statistics is an excellent way to go from zero to a good overview of the basics with a minimum of hard math. After that, if you're mostly interested in applying basic techniques to your own stuff, you want a good undergrad textbook. I don't have any good recommendations here, unfortunately. If you have a good math background (or are motivated to get it) and you want to keep going, Statistical Models; Theory and Practice by David A. Freedman (http://www.amazon.com/review/R2XUNM92KYU7BB http://www.amazon.com/review/R2XUNM92KYU7BB) has the math, the philosophy, the hands on analysis of studies, and the exercises to put you in a better position to evaluate statistical research than some people who produce it.

physcab 17y ago

The key is to come up with a well-formulated question, such as "I wonder if I can predict stock trends." Then in doing so, you'll search the web and come across predictive modeling, which will lead to machine learning techniques, which will lead to good resources. Within those machine learning sources, search for chapters on prediction and classification, and you'll come across regression techniques, support vector machines, relevance vector machines, etc. Then you'll wonder, "ok, how do I actually solve this problem" so you may search for "SVM implementations" and find Steve Gunn's for Matlab for example. Then after much codebanging, you'll realize that inorder to solve this problem, you need a good dataset, so you go to Yahoo finance and see if you can download some data for IBM. This is usually the process one needs to follow, albeit with some intermediate steps switched out for others here and there.

discojesus 17y ago
it seems like if he did that, he'd be biting off WAY more than he can chew at the present time. If you want to learn statistics, it's probably better to start at the beginning (_Cartoon Guide to Statistics_, O'Reilly's new _Head First Statistics_, or Huff's _How to Lie With Statistics_) than to leap headlong into a huge, mostly intractable problem and pagefault in knowledge at each point you come across something you don't know how to do.
- physcab 17y ago
  I agree, but at the same time, you only learn by doing. In my experience, even when you dive in way over your head, you tend to pick up the information rather quickly. I took a machine learning class with no statistics background and after a few weeks of floundering and learning terminology I was fine. The benefit of forming a problem first gives you an ultimate goal of which to work towards. Don't tell Google that it's slogan ("Organize the world's information") is biting off more than it could chew.
  - timwiseman 17y ago
    I agree with you, starting with a problem can help provide motivation, structure, and focus and all of those can help keep you learning quickly. Still, there is a place for an introductory book if you are truly coming from minimal knowledge of the subject.

tokenadult 17y ago

My two favorite orientations to what statistics is all about are two free articles on the Web. Both recommend books for further reading, and they are good books. "Advice to Mathematics Teachers on Evaluating Introductory Statistics Textbooks" http://statland.org/MyPapers/MAAFIXED.PDF http://statland.org/MyPapers/MAAFIXED.PDF "The Introductory Statistics Course: A Ptolemaic Curriculum?" http://repositories.cdlib.org/cgi/viewcontent.cgi?article=1002&context=uclastat/cts/tise http://repositories.cdlib.org/cgi/viewcontent.cgi?article=10... Here's a list of the best beginning textbooks: http://www.mrderksen.com/textbooks.htm http://www.mrderksen.com/textbooks.htm

timwiseman 17y ago

It is only a brief introduction and should be nothing more than a starting point, but "The Manga Guide To Statistics" http://www.amazon.com/Manga-Guide-Statistics-Shin-Takahashi/dp/1593271891/ref=sr_1_1?ie=UTF8&qid=1249566654&sr=8-1 http://www.amazon.com/Manga-Guide-Statistics-Shin-Takahashi/... is a good first book.

tel 17y ago

Physcab suggests a great step #2: diving into some real statistics problems. The information available online today is more than at that point. Step #1 is going to be getting the foundations so that you can quickly digest the meaning and purpose of things like machine learning. Fortunately, statistics can be largely summarized as "the science/math/art of explaining variance". Study what variance is and means and you'll dive through probability, distributions, modeling, inference, prediction, parametrization, simulation, and all of those fun topics while keeping an understanding for why they exist. Finally, I'd highly suggest taking a look at Tufte's work because once you understand variance, you've still got to explain it.

bravura 17y ago

Get the machine learning book by Bishop.

stanleydrew 17y ago

I highly recommend Hayashi's book on Econometrics. It's what we used in the first year of my PhD program in Economics. But it's probably worth starting with a basic probability and statistics book, preferably one that's pretty mathematical. I've used Hogg McKean and Craig's Introduction to Mathematical Statistics and it's really good.

mbrubeck 17y ago

O'Reilly's Statistics In a Nutshell is quite good as both a textbook and a reference. I'm (slowly) working through it on my own.