The Curious Engineer

mathbabe

2011–2012

575 posts

2013–2026 →

2012 376

December 2012

  1. I totally trust experts, actually
  2. On trusting experts, climate change research, and scientific translators
  3. Open data is not a panacea
  4. Suggested New Year’s resolution: start a blog
  5. Corporations don’t act like people
  6. Consumer segmentation taken to the extreme
  7. Whom can you trust?
  8. Nate Silver confuses cause and effect, ends up defending corruption
  9. Empathy, murder, and the NRA
  10. If Barofsky heads the SEC I’ll work for it
  11. Making math beautiful with XyJax
  12. Silicon Valley: VC versus startup culture
  13. Aunt Pythia’s advice
  14. MOOCs and calculus
  15. MOOC is here to stay, professors will have to find another job
  16. When accurate modeling is not good
  17. Fighting the information war (but only on behalf of rich people)
  18. Columbia Data Science course, week 14: Presentations
  19. Costco visit
  20. Aunt Pythia’s advice
  21. How math departments hire faculty
  22. Unequal or Unfair: Which Is Worse?
  23. Can we put an ass-kicking skeptic in charge of the SEC?
  24. Diophantus and the math arXiv
  25. How do we quantitatively foster leadership?
  26. Aunt Pythia’s advice

November 2012

  1. How to build a model that will be gamed
  2. Columbia Data Science course, week 13: MapReduce
  3. Rolling Jubilee is a better idea than the lottery
  4. How to evaluate a black box financial system
  5. On Reuters talking about Occupy
  6. Systematized racism in online advertising, part 1
  7. Aunt Pythia’s advice and a request for cool math books
  8. It’s Pro-American to be Anti-Christmas
  9. A primer on time wasting
  10. Black Friday resistance plan
  11. Columbia Data Science course, week 12: Predictive modeling, data leakage, model evaluation
  12. Whither the fake clicks?
  13. Support Naked Capitalism
  14. Aunt Pythia’s advice
  15. O’Reilly book deal signed for “Doing Data Science”
  16. Columbia Data Science course, week 11: Estimating causal effects
  17. The ABC Conjecture has not been proved
  18. Data science in the natural sciences
  19. Anti-black Friday ideas? (#OWS)
  20. Free people from their debt: Rolling Jubilee (#OWS)
  21. Aunt Pythia’s advice
  22. Medical research needs an independent modeling panel
  23. Columbia Data Science course, week 10: Observational studies, confounders, epidemiology
  24. When are taxes low enough?
  25. Money market regulation: a letter to Geithner and Schapiro from #OWS Occupy the SEC and Alternative Banking
  26. The NYC subway, Aunt Pythia, my zits, and Louis CK
  27. The zit model
  28. Ask Aunt Pythia
  29. Columbia Data Science course, week 9: Morningside Analytics, network analysis, data journalism

October 2012

  1. Occupy in the Financial Times
  2. The definitive visualization for Hurricane Sandy, if you’re a parent of small children
  3. An AMS panel to examine public math models?
  4. Columbia Data Science course, week 8: Data visualization, broadening the definition of data science, Square, fraud detection
  5. On my way to AGNES
  6. For the nerds: what’s wrong with this picture?
  7. Strata: one down, one to go
  8. How to measure a tree
  9. We’re not just predicting the future, we’re causing the future
  10. Are healthcare costs really skyrocketing?
  11. Amazon’s binder reviews
  12. Birdwatching
  13. What’s a fair price?
  14. Columbia Data Science course, week 7: Hunch.com, recommendation engines, SVD, alternating least squares, convexity, filter bubbles
  15. Growing old: better than the alternatives
  16. Causal versus causal
  17. Gaming the Google mail filter and the modeling feedback loop
  18. The investigative mathematical journalist
  19. Philanthropy can do better than Rajat Gupta
  20. Personal privacy and institutional transparency
  21. Columbia Data Science course, week 6: Kaggle, crowd-sourcing, decision trees, random forests, social networks, and experimental design
  22. Live and let live, motherfuckers
  23. Neil Barofsky on the Fed Stress Test
  24. Suresh Naidu: analyzing the language of political partisanship
  25. The Neighbors
  26. Dissolve the SEC
  27. Columbia Data Science course, week 5: GetGlue, time series, financial modeling, advanced regression, and ethics
  28. Next-Gen Data Scientists
  29. Knitting porn
  30. Bad news wish list
  31. Student loans are a regressive tax
  32. High frequency trading: how it happened, what’s wrong with it, and what we should do

September 2012

  1. Telling people to leave finance
  2. A Few Words on the Soul
  3. What is a model?
  4. Columbia Data Science course, week 4: K-means, Classifiers, Logistic Regression, Evaluation
  5. Evaluating professor evaluations
  6. Filter Bubble
  7. Columbia Data Science course, week 3: Naive Bayes, Laplace Smoothing, and scraping data off the web
  8. Am I the sexiest thing about the 21st century?
  9. We are the 47%
  10. Two rants about hiring a data scientist
  11. Emanuel Derman’s Apologia Pro Vita Sua
  12. The Debt Resistors’ Operation Manual
  13. Occupy Wall Street is one year old
  14. Why are the Chicago public school teachers on strike?
  15. Columbia data science course, week 2: RealDirect, linear regression, k-nearest neighbors
  16. Pruning doesn’t do much
  17. Yesterday
  18. NYC Parks datadive update: does pruning prevent future fallen trees?
  19. Datadive: NYC Park data
  20. How is math used outside academia?
  21. Columbia data science course, week 1: what is data science?
  22. Videos and a love note
  23. 52 Shades of Greed cards fundraiser now up: please help! (#OWS)
  24. STEM jobs and the economy
  25. Women, marriages, and the rat-race
  26. Fair versus equal
  27. Stuff you might want to know about

August 2012

  1. Automated call centers and superorganisms
  2. Citigroup’s plutonomy memos
  3. School starts next week
  4. The country is going to hell, whaddya gonna do.
  5. What makes us fat
  6. #OWS update
  7. NSA mathematicians
  8. Explain your revenue model to me so I’ll know how I’m paying for this free service
  9. When to quit your nerd job
  10. Someone didn’t get the memo about regulatory capture
  11. The U.S. Treasury is a bad baby daddy
  12. Another death spiral of modeling: e-scores
  13. Update on organic food
  14. Away for a week – will miss you
  15. Subway etiquette: applying makeup on the 1 train
  16. Datadive weekend with DataKind September 7-9
  17. Looterism
  18. High frequency trading: does it hurt the little guy?
  19. I love whistleblowers
  20. What is a proof?
  21. Bailout, the book
  22. Le Monde article (#OWS)
  23. Why the internet is creepy
  24. VAM shouldn’t be used for tenure
  25. Gangnam Style

July 2012

  1. Statisticians aren’t the problem for data science. The real problem is too many posers
  2. Columbia Data Science Institute: it’s gonna happen
  3. The douche burger, and putting a ruler to the dick.
  4. Does mathematics have a place in higher education?
  5. Income distributions and misleading poll questions (#OWS)
  6. Why is LIBOR such a big deal? (#OWS)
  7. Is open data a good thing?
  8. Today is a day for politics
  9. A call to Occupy: we should listen.
  10. Tu-du leest bork bork
  11. Exploit me some more please
  12. HCSSiM Workshop day 17
  13. HCSSiM Workshop day 16
  14. HCSSiM Workshop day 15
  15. HCSSiM Workshop, day 14
  16. HCSSiM Workshop, day 13
  17. Yellow Pig Carols
  18. HCSSiM Workshop, day 12
  19. HCSSiM Workshop, day 11
  20. It rocks to be 40
  21. HCSSiM Workshop day 10
  22. How to lie with statistics, Merck style
  23. HCSSiM Workshop day 9
  24. Mathematicians know how to admit they’re wrong
  25. HCSSiM Workshop day 8
  26. HCSSiM Workshop day 7
  27. Center for Popular Economics Summer Institute 2012
  28. Toilet paper rant
  29. HCSSiM Workshop day 6
  30. HCSSiM Workshop day 5
  31. HCSSiM Workshop day 4
  32. Nim
  33. HCSSiM Workshop day 3
  34. HCSSiM Workshop day 2
  35. HCSSiM workshop day 1
  36. How much of data science is busy work?
  37. Mixing colors: pigment vs. light

June 2012

  1. Analemma
  2. Is a $100,000 pension outrageous?
  3. Free online classes: the next thing
  4. The basic unit is risk
  5. Why are pharmaceutical companies allowed to do their own trials?
  6. Coding is like being in a band
  7. Is science a girl thing?
  8. Saturday morning reading
  9. Quants, Models, and the Blame Game
  10. Please don’t have any kids
  11. Who should be on the Fed Bank Boards? #OpenFed
  12. Jamie Dimon gets a happy ending massage at Banking Committee hearing
  13. Stop and Frisk silent march today
  14. On being an alpha female
  15. Germany’s risk
  16. My followership problem
  17. Using retirement money now
  18. Questions for Jamie Dimon
  19. I don’t trust politicians more than I trust bankers
  20. Happy Birthday to me!
  21. The fake problem of fake geek girls, and how to be a sexy man nerd
  22. Personal Democracy Hackathon today
  23. Hangover cure
  24. What if the bond markets priced in actual risk?
  25. Who will Regulate the Superheroes on Wall Street?
  26. Regulation is not a dirty word
  27. Combining priors and downweighting in linear regression
  28. An easy way to think about priors on linear regression
  29. A low Fed rate: what does it mean for the 99%?
  30. One language to rule them all

May 2012

  1. Best case/ worst case: Medicine 50 years from now
  2. How to talk conservative
  3. When “extend and pretend” becomes “delay and pray”
  4. Biking in New York City
  5. Everybody lies (except me)
  6. All the good data nowadays is private – what’s the point of having a data science Ph.D.?
  7. Favorite bands
  8. The engaged skeptic
  9. An open source credit rating agency now exists!
  10. Buying organic doesn’t make you better than me
  11. Stop, Question, and Frisk policy getting stopped, questioned, and frisked
  12. WTF with girdles?!?
  13. Google’s promotion policy sucks for women
  14. Recovery begins when addiction ends: an open letter to Jamie Dimon (#OWS)
  15. Stop with the man-diets already, coffee is good for you.
  16. The modeling death spiral for public schools
  17. Tech firm mindset to avoid like the plague
  18. Who wants Jamie Dimon’s job?
  19. Ideas for two thesis problems in data science
  20. Conspiracy theorists may be right but they can’t explain why
  21. Evil finance should contribute to open source
  22. Privacy concerns
  23. To my Libertarian friends
  24. How are you a narcissist?
  25. Performing tomorrow night with Reno
  26. The meritocracy myth
  27. Being a single mom is not a crime
  28. Great news for NYC dataphiles: Microsoft Research is coming to NYC
  29. Occupy Data!
  30. The student debt crisis
  31. It’s May Day!

April 2012

  1. Conclusion (#OWS)
  2. NYC Data Hackathon
  3. An Intervention (#OWS)
  4. The Addiction (#OWS)
  5. In Denial (#OWS)
  6. Innovation, elevation, and space travel
  7. Hey, Doocy apologized for fabricating part of Obama’s speech!
  8. Declaration of Linear Independence: the nerdiest thing you’ve ever seen
  9. Online learning promotes passivity
  10. Fox News fabricates a part of Obama’s speech
  11. Occupy Wall Street isn’t dead
  12. What’s fair?
  13. Are politicians failing our lobbyists? (Onion news)
  14. Powerpoint kills me from within my soul
  15. Reputational risk is insufficient for ratings agencies
  16. Can clouds think?
  17. The Great Wealth Transfer, late 1900’s to early 2000’s (part 1)
  18. Get overpaid so people will listen to you
  19. #OWS update: looking for UX help
  20. Should we have a ratings agency for scientific theories?
  21. How to teach someone how to prove something
  22. Calling all data scientists! The first ever global data science hackathon
  23. In which mathbabe becomes insurance claims adjuster
  24. Continuously forecasting
  25. On the making of a girl nerd
  26. Who is the market?
  27. More creepy models
  28. It sucks to be rich
  29. Thought experiment: witness protection program
  30. Who here reads Dutch? (#OWS)
  31. The muppets strike back
  32. What is innovation?

March 2012

  1. Parents: don’t put your kid on a diet
  2. Vote with your wallet
  3. What’s Mahout?
  4. How informed does an opinion have to be before it’s taken seriously?
  5. On NPR’s Morning Edition (#OWS)
  6. Bloomberg joins Occupy Wall Street
  7. Random stuff, some good some bad
  8. I regret nothing
  9. The Market Price of Privacy
  10. Today is Sonia Kovalevsky Day
  11. The higher education bubble
  12. Supply side economics and human nature
  13. Which muppet are you?
  14. Recruiting against Goldman Sachs
  15. Calligraphy of geese
  16. Hip Hop’s Cambrian Explosion: Part 3
  17. Propaganda with a Caveat
  18. Interlude: Egret Ardor
  19. Hip Hop’s Cambrian Explosion: Part 2
  20. Interlude: Newt Haiku
  21. Hip Hop’s Cambrian Explosion: Part 1
  22. Why Larry Summers lost the presidency of Harvard
  23. VAM versus what?
  24. Sausage Wall
  25. Quants for the rest of us
  26. Versus what?
  27. The Value Added Teacher Model Sucks
  28. Why experts?
  29. Do not track vs. don’t track
  30. Charity auctions and hate crimes
  31. This is water
  32. Open Models (part 2)

February 2012

  1. Economists don’t understand the financial system
  2. Vikram Pandit: let’s talk
  3. Math-Startup Collaborative at Columbia tomorrow
  4. Math teaching needs overhaul
  5. Teaching scores released
  6. I am the most boring person in the world
  7. It’s all mom’s fault
  8. Model Thinking (part 2)
  9. #OWS Alternative Banking update
  10. Creepy model watch
  11. What data science _should_ be doing
  12. Why I love nerds
  13. Sunday morning music videos
  14. ECB trades crap for slightly less crappy crap
  15. How Harvard is failing its students
  16. A modeled student
  17. How Big Pharma Cooks Data: The Case of Vioxx and Heart Disease
  18. Today is Volcker Day
  19. Mathematics has an Occupy moment
  20. New online course: model thinking
  21. How unsupervised is unsupervised learning?
  22. What’s going on: Greece and mortgages
  23. The future of academic publishing
  24. As predicted: watered down insider trading bill
  25. #OWS upcoming events
  26. This month’s Sky Mall: a sneak peek
  27. More Money than God
  28. Politicians and insider trading
  29. Preggers
  30. Opacity, noise, and overpopulation in finance
  31. Women in math
  32. Raise capital gains and stop flying
  33. Data Science needs more pedagogy
  34. The SEC needs handcuffs
  35. Let them game the model
  36. CDS data and open source ratings
  37. Alternative Banking in FT Alphaville (#OWS)

January 2012

  1. Econned and Magnetar
  2. Freddie Mac: worse than hedge funds?
  3. Medical identifiers
  4. Complexity and transparency in finance
  5. “Where to start?”, I wondered.
  6. Does hip-hop still exist?
  7. Sturgeon
  8. WTF: Greek debt vs. CDS
  9. Updating your big data model
  10. Brainstorming with narcissists
  11. Mortgage settlement talks
  12. Occupy the World Economic Forum
  13. Seasonally adjusted news
  14. Data Scientist degree programs
  15. Bad statistics debunked: serial killers and cervixes
  16. Apologies to Adam Smith
  17. How’s it going with the Volcker Rule?
  18. Followup: Change academic publishing
  19. Change academic publishing
  20. Happy Birthday, Betty White!
  21. Quantitative analysis of regulatory capture
  22. Puzzle blog
  23. Sunday Links
  24. High Frequency Trading and Transaction Taxes
  25. Shareholder value and Adam Smith
  26. Happy Baconmas!
  27. Open Models (part 1)
  28. The Waltons’ money
  29. CBC Radio
  30. #OWS news
  31. #Occupy Wall Street course at Columbia University: update
  32. Who the hell is buying European debt?
  33. It takes imagination to be boring
  34. Politics of teacher pay disguised as data science
  35. Ken Ribet’s love note from Serge Lang
  36. Differential privacy
  37. #Occupy Wall Street course at Columbia University
  38. The sin of debt (part 3)

2011 199

December 2011

  1. A New Year’s resolution you can keep
  2. Matt Stoller explains politics
  3. Information loss
  4. Economist versus quant
  5. Is Stop, Question and Frisk racist?
  6. A good data scientist is hard to find
  7. Steam queen
  8. Crappy modeling
  9. Need your vote
  10. Why work?
  11. How to challenge the SEC
  12. Bloomberg engineering competition goes to Cornell
  13. A rising tide lifts which boats?
  14. Bloomberg engineering competition gets exciting
  15. What up, New York Times? (#OWS)
  16. Where is Volcker’s letter? (#OWS)
  17. Privacy vs. openness
  18. The sin of debt (part 2)
  19. Conservation Law of Money
  20. Resampling
  21. Thank you, Inside Job
  22. Meritocracy and horizon bias
  23. ISDA has a blog!
  24. #OWS data nerd
  25. Good bank/ bad bank – why we didn’t do it
  26. Crowdsourcing projects
  27. Quantitative theory of blogging
  28. Hank Paulson
  29. Various #OWS links

November 2011

  1. Correlated trades
  2. Two pieces of good news
  3. Regulation arbitrage, the Volcker Rule, and TBTF (#OWS)
  4. No gifts, please
  5. Two poems
  6. Sing with me! (#OWS)
  7. ‘Move Your Money’ app (#OWS)
  8. What’s the Volcker Rule?
  9. Who takes risks?
  10. What does “too big to fail” mean?
  11. Alternative Banking meeting today
  12. Occupy the SEC: commenting on the Volcker Rule
  13. Protest today
  14. In memory of Sally Hale
  15. Zuccotti Park just now: updated
  16. Hey Google, do less evil.
  17. Morning poem
  18. Postage paid protest
  19. The sin of debt
  20. Overfitting
  21. #Occupy Wall Street meeting and news
  22. In praise of nerd kids
  23. Gaming the system
  24. Truth Values
  25. Why I’m involved with #Occupy Wall Street
  26. The Numbers are in: Round 1 to #OWS
  27. Open Forum speeches
  28. #OWS meeting tomorrow
  29. Quantitative tax modeling?
  30. Towards a better financial system

October 2011

  1. #OWS Alternative Banking update
  2. #OWS Alternative Banking meeting today
  3. Data Science and Engineering at Columbia?
  4. Open Forum next Friday
  5. Is Big Data Evil?
  6. What’s your short list of actionable complaints?
  7. Emanuel Derman’s Models.Behaving.Badly.
  8. Shareholder Value
  9. Credit Unions in NYC flyer
  10. Why Credit Unions? (#OWS) (part 1)
  11. Math in Business
  12. Some really terrible ideas
  13. Topology of financial modeling
  14. David Graeber on Occupy Wall Street
  15. Alternative Banking System
  16. What is a Credit Union? (#OWS)
  17. Datadive update
  18. NYCLU: Stop Question and Frisk data
  19. Data Without Borders: datadive weekend!
  20. Wall Street and the protests
  21. Occupy Wall Street flyer
  22. Bayesian regressions (part 2)
  23. Koo: don’t be surprised by the crappy economy
  24. What’s wrong with Wall Street and what should be done about it?
  25. Saturday afternoon quickie
  26. Habits
  27. Financial Terms Dictionary
  28. Bayesian regressions (part 1)
  29. My friend the coffee douche
  30. Data science: tools vs. craft
  31. “Our organization does not reward failure” – Koch
  32. First day of calculus class
  33. Is the Onion actually America’s finest news source?
  34. Mortar Hawk: hadoop made easy

September 2011

  1. Occupy Wall Street: Day 13
  2. Go Rays!
  3. Never apologize
  4. Occupy Wall Street—Report
  5. The flat screen TV phenomenon
  6. Why and how to hire a data scientist for your business
  7. I never sit on the subway
  8. In German beard circles, tensions are high.
  9. Are SAT scores going down?
  10. Do higher taxes kill jobs?
  11. Back from Strata Jumpstart
  12. How do you standardize tests?
  13. What the hell is going on in Europe?
  14. Household debt amnesty?
  15. Guest Post: What is a family?
  16. Politics: the good news and the bad news
  17. The pandas module and the IPython notebook
  18. What are the chances that this will work?
  19. Monday morning links
  20. Working with Larry Summers (part 3)
  21. Meetups
  22. Debt
  23. Some cool links
  24. Guest post: The gold standard
  25. What is “publicly available data”?
  26. The reckoning
  27. Back
  28. I don’t want to live forever
  29. Good for the IASB!

August 2011

  1. Strata data conference
  2. Why log returns?
  3. We didn’t make money on TARP!
  4. What is the mission statement of the mathematician?
  5. Lagged autocorrelation plots
  6. Should short selling be banned?
  7. Want my advice?
  8. Demographics: sexier than you think
  9. Karaoke
  10. Machine learners are spoiled for data
  11. Is willpower a quantifiable resource?
  12. How the Value-Added Model sucks
  13. What’s with errorbars?
  14. I.P.O. pops
  15. Default probabilities and recovery rates
  16. Are Corporations People?
  17. Open Source Ratings Model (Part 2)
  18. Open Source Ratings Model?
  19. The Life Cycle of a Hedge Fund
  20. Wall Street versus us
  21. Monday morning reading list
  22. Data Viz
  23. Adam Smith made me buy a Kindle
  24. Why should you care about statistical modeling?
  25. Some R code and a data mining book
  26. How do you disagree?
  27. Cool example of Bayesian methods applied to education
  28. Why didn’t anybody invite me!?

July 2011

  1. What kind of math nerd job should you have?
  2. Three strikes against the mortgage industry
  3. Historical volatility on the S&P index
  4. Is too big to fail a good thing?
  5. Elizabeth Warren: Moses and the Promised Land
  6. Quit your job and become a data miner!?
  7. The Bad Food Tax
  8. Measuring historical volatility
  9. Happiest being sad
  10. What tensor products taught me about living my life
  11. Follow up on: math contests kind of suck
  12. _Love_ you people
  13. High frequency trading: Update
  14. High frequency trading
  15. Math contests kind of suck
  16. What is an earnings surprise?
  17. I love math nerd kids
  18. Motivating transparency: what we could do about too big to fail
  19. Bank accounting link
  20. Short Post!
  21. Weekend Reading
  22. Adding-up rules and Hockey Sticks
  23. Does an academic job in math really suck?
  24. Glucose Prediction Model: absorption curves and dirty data
  25. Cookies
  26. Fair Foods
  27. Did you have a happy childhood?
  28. Asymmetrical Information

June 2011

  1. Women on a board of directors: let’s use Bayesian inference
  2. Cora Sadosky
  3. Woohoo!
  4. Better risk modeling: motivating transparency
  5. Women on S&P500 boards of directors
  6. Step 0 Revisited: Doing it in R
  7. Working with Larry Summers (part 2)
  8. Did someone say regulation?
  9. Inspirational speech for women in math
  10. Step 0: Installing python and visualizing data
  11. Data Without Borders
  12. Guest post: Tax Repatriation Day
  13. Quantitative risk management
  14. The Greek situation
  15. Data mining contests
  16. The basics of quantitative modeling
  17. Working with Larry Summers (part 1)
  18. Why “mathbabe”?
  19. What is seasonal adjustment?
  20. What’s it take to be a woman in math?
  21. Hello world! [stet]

2013–2026 →