That’s such an obvious concept—that there are all kinds of wonderful new inventions that give you nothing as owners except the opportunity to spend a lot more money in a business that’s still going to be lousy. The money still won’t come to you. All of the advantages from great improvements are going to flow through to the customers.
The great lesson in microeconomics is to discriminate between when technology is going to help you and when it’s going to kill you. And most people do not get this straight in their heads. But a fellow like Buffett does.
For example, when we were in the textile business, which is a terrible commodity business, we were making low-end textiles—which are a real commodity product. And one day, the people came to Warren and said, “They’ve invented a new loom that we think will do twice as much work as our old ones
Please read the Disclaimers at the end of the post first, if you’re easily offended.
- Get extremely unbeatable at 20 Questions(rationality link). It’ll help you make your initial diagnoses(ones based on questions about symptoms) faster and more accurate.
- Understand probability, bayes theorem and how to apply it** This will help you interpret the test results, you ordered based on the 20 questions.
- Understand base rate fallacy, and how to avoid being over confident.
- Practice enough of systems thinking in your diagnoses and prognoses thought-experiments. May be even try it in other domains to check your skill level. And for extra credits learn some of the basics of dynamical sytems***, as the human body is one.
- Understand the upsides and downsides of the drugs you prescribe. Know the probabilities of fatal and adverse side-effects and update them with evidence(Bayes’ theorem mentioned above) as you try out different brands and combinations.
- Know the costs and benefits of any treatment and help the patient make a good decision based on the cost-benefit analysis of treatment combined with the probabilities of outcome.
- Ask and Keep a history of medical records and allergies of the patient and till their grand parents.*
- Be willing and able to judge, when a patient is better off with a specialist. Try to keep in touch with Doctors nearby and hopeful all types of specialists.
- Explain the treatment options and pros and cons in easy language to the patients. It’ll reduce misunderstandings and eventually dis-satisfaction with the treatment.
- Resist the urge to treat patients as NPCs. Involve them in the treatment process.
- Find a hobby, that you can keep improving on till the end of life.
- Be aware of the conflict of interest between the patient and the pharmaceutical companies.
- Have enough research skills to form opinions on base rates/probabilities in different diseases and treatment methods as needed.
- If you’re in a big hospital setup, make sure you’ve the best hospital administration, if not find ways to improve or find better big hospital.
- Medical expertise is only relevant once you see the patient. Your ability to judge the evidence requires getting access to it; this means you need to be able to correctly send requests, get the data back, and keep all this attached to the correct patient.Scheduling, filing and communication. Lacking these, medical expertise is meaningless.
- Be aware of cognitive biases humans are liable to make.
Basically the same skill sets as above. One difference is in the skill level and you should customize that as needed.
- For ex: You would need to be able to explain the treatment options and the probabilistic nature of the outcomes to your patients.
- As for research, keep a track of progress in your area in treatment methods and different outcomes on the “quality of life” for the patients after the treatment.
- Better applied Bayesian skills. In the sense of figuring out independent variables and their probabilities affecting the outcome.
Some controversial ideas(Better use your common-sense before trying out):
- Experiment a little with your bio-chemistry and see how they affect your thought-processes. To be safe, stick to biologically produced ones. For ex: injecting self with a small adrenalin dose and monitoring bodily response can help keep your thinking clear in emergency situations.
- Know your self biology better. For ex: male vs female differences mean the adrenalin response is different and peaks later in females. If you think that’s wrong, please go back and check your course work. Also watch this 2 hour video and come back with objections after reading the studies he quotes.
- Keep regularly(whatever frequency your practice and nature of work demands) checking your(for ex; hormone levels) blood states, so that you can start regulating your self for optimal decision-making skills.
- If you’re a woman, you’ll customize practice on some of the skill sets above differently. For ex: Mastery over emotions might need more practice, while empathizing/connecting with the patient might be easier.
- Most of what follows is based on my experiences(either as a patient myself or a concerned relative) with Indian Doctors. Some of it may be trivial, to others, but most of it is skills a doc will need and ignored in school.
- I’ve split it in two (specialists and generalists) but there’s a fair amount of overlap.
- These are fairly high standards, but worth shooting for and I’ve kept the focus on smart rather than hard work.
- I’ve stayed from a few topics like: bedside manners/social skills, specific medical treatments and conditions(obviously, I’m not a Doctor after all) and a few others, you can add/delete(also specify/pick levels) as you see fit.
- Pick the skill-levels as demanded by your client population and adjust.
- I’m assuming generalists, don’t have to deal with emergency cases, but in some parts, that’s not likely then pick common emergency categories and follow specialist advice.
- My qualifications are basic mechanical engineering plus a master’s in cognitive science. By their nature, I’ve a very shallow knowledge/overview of the topics involved, but too little certainty for me to give any specific advice.
- I wrote this based on my experiences and with humans in mind, but veterinary Doctors may find some useful too.
- — I understand this is difficult in Indian circumstances, but I’ve seen it being done manually(simply leaves of prescriptions organized alphabetically, link to dr.rathinavel) , so it’s possible and worth the effort unless, you practice in area of highly migratory population.(for example rural vs urban areas).
**– If you’re trying to compete on availability for consultation, you’ll need to be able to do this after being woken in the middle of the night.
*** — Please don’t take this literally. Though I’m optimistic that dynamical system tools may be enough to describe the human body, it might turn out human body is more dynamic than them. In other words, use your judgement, and make sure you can apply the dynamical systems theory to say “three-body problem“
- Child-birth or labour involves physical trauma, but it is expected to happen (for say 9 months)… that complicates things???? (It definitely breeds paranoia and worry-downward-spiral)
- However, the fact that it is expected and the fact that it is linked to species survival has facilitated a lot of research. I tend to think expected and predictable events get a bit over-researched and over-operationalized* in general. Is the fact that it is linked to reproduction causes too much(harmful) research or not?? Interesting question, but may not be answerable…
- The choice of word “labour” is interesting. It has marxist/communist connotations in most contexts, but in this, not really…. coincidence???
- The blanket ban of “no males in labour ward”** might be useful and valid, but it hardly is without exception and definitely allows for more follow-the-process decisions, encouraging a ignorance of context..
- Even after about 30 hours of partial sleep and adrenaline surge*** I could feel that jump in heart beat on looking at my daughter..
- P.S: every note above(except 5th) was written before the adrenaline surge.
* — to the point of over-engineering that risks violating the “do-no-evil”
***–which was another story, i’ll write after my lymbic system settles down(aka down-regulating-lymbic-system for that memory), suffice it to say, i became more convinced of gender-difference (aka sexist)
The 3 common measures of central tendency used in statistics are :
- 1. Mean
- 2. Median
- 3. Mode
Note: That all these three and the other measures do obey the basic rules of measure theory.
The point being what you choose to describe your central tendency is key and should be decided based on what you want to do with it. Or more precisely what exactly do you want to optimize your process/setup/workflow for, and based on that you’ll have to choose the right measure. If you read that post above you’ll understand that:
- Mean — Mean is a good choice when you want to minimize the variance(aka, squared distance or second statistical moment about central tendency measure).. That’s to say your optimization function is dominated by a lot of square of distance(from central tendency measure) terms. Think of lowering mean squared error. and how it’s used in straight line fitting
- Median — Median is more useful if your optimization function has distance terms but not squared ones. So this will in effect be the choice when you want to minimize the distance from central tendency.
- Midrange — Midrange is useful when your function looks like max(distance from central measure)..
If most of that sounded too abstract then here’s a practical application I can think of right away to use. Imagine you’re doing performance testing and optimization of a small API you’ve built. Now I don’t want to go into what kind of API/technology behind it or anything. So let’s just assume you want to run it multiple times and calculate a measure of central tendency from it and then try to modify the code’s performance(with profiling + different libraries/data structures whatever….), so what measure of central tendency should you pick?
- Mean — Most Engineers would pick Mean and in a lot of cases it’s enough but think about it. It optimizes for variance of run/execution time. Which is important and useful to optimize in most cases, but in some cases may not be that important.
- Mode — An example is if your system is a small component of say a high-frequency trading platform and the consumer of it has a timeout and fails if it times out.(aka your api is mission-critical, it simply cannot fail). Then you want to make sure even in the lowest case your program completes. If the worst case runtime complexity is what you want to lower then you should pick mode. (Note this is still a trade-off over not lowering the average/mean use-case, just like hard-choice.)
- Median — This is very similar to Mean, except it doesn’t really care about variance. If you’re picking median, then your optimized program is sure to have the best performance in the average run/case/dataset
- Midrange — Well this is an interesting case. Think about it.. even in the previous timeout example i mentioned this could be useful. Here it goes,suppose your api is not mission-critical(i.e: if it fails the overall algorithm will just throw out that data term and progress with other data sources). when you want to maximize the number of times your program finishes within the timeout. i.e: you’re purely measuring the number of times you finish/return a value within the timeout period. You don’t care about the worst-case scenario.
There are other measures, such as:
Additionally, you can take mean of functions(non-negative ones too). See JDCook’s blog again.
I hope there’s another window in case of an emergency. Just saying.
Here’s a pdf or writing by NNT arguing the reasoning of violence is going down ignores the outliers, but that is not an acceptable assumption.
UPDATE: On a bit of thought, I realize that’s not explicitly argued, but only
implied, nay inferred by me, due some of historical writing.
UPDATE 2: The original article can be crudely summarized as, the way Steven Pinker has eliminated the outliers(like wars) is valid only for a distribution that’s known to approximate the normal distribution, but not for a fat-tailed distribution and violence is closer to being fat-tailed than normal distribution.
A great presentation on thermoelectrics Akram Boukai is a researcher in material science, and an expert on converting heat to electric energy: thermoelectrics. Today I wish to talk about a beautiful presentation he just gave at TTI/Vanguard in San Francisco.
Full Disclosure: I’m biased against facebook due to my previous experiences having an account on facebook. And have strong interests in net neutrality.
Now on to the survey that FB PR team cites. taken from here.
I was reading Mahesh murthy’s post about the big ‘net neutrality vs free basics’ debate and came across this link that FB seems to cite for claiming most indians want the “Free Facebook” plan. So I tried to dig in to the survey details and here are my criticisms.
Survey methodology A national survey was conducted in November and December 2015 with a representative sample of 3,094 adult residents of India. The margin of error is 1.8%. The survey was conducted door-to-door throughout the country of India. The sample reflects the full diversity of the regions and states of India, and was conducted with a full representation of large cities, small cities, towns, villages, and rural areas. The sample reflects the population of India with respect to age, gender, and other demographic variables.
I’ll withold comments on the summary part. But let’s talk about the Methodology:
Representative sample of adult residents of India:
The country’s population is 1 billion. ~3100 people out of it is not representative no matter what magic sampling method you use.
Margin of error is 1.8%:
Ermmm.. Thats’ interesting, but can you please tell us how you came up with that number?
The sample reflects the full diversity of the regions and states of India, and was conducted with a full representation of large cities, small cities, towns, villages, and rural areas. The sample reflects the population of India with respect to age, gender, and other demographic variables.
Now, I’m convinced you guys have read the book “How to lie with statistics?”* Seriously, can you provide some split of how many of those 3094 survey participants live in a small city, town, village, rural area, large city. Also can you provide us the split/pivot tables based on age, gender and these other demographic variables you used to decide it was a representative sample.
Alright, that’s it based on what they have provided. Now more on what they’ve not provided or what I’d like to see if I’m expected to make a policy decision based on a survey.
Null Hypothesis they decided to test [based on which they should have designed the survey questionnaire].
Sample size determination: Now it’s not clear from the press release but may be this is what they refer to as error margin. Namely they chose a confidence interval of 1.8% to arrive at a sample size?
No mention of what, if any statistical test they used. My suspicion is that they ran some but didn’t like the p-values and confidence interval, they gave, so decided not to report.
Perhaps the most important, the actual phrasing of the questions was decided before hand or just verbally improvised. Given the language diversity, it might be acceptable to verbally improvise, but that would simply double[or more precisely no.of.languages x times] the ideal sample size.
By the way, the number other categorical variables [like they mention, age, gender, urban/rural/town/city , etc..] each of them would multiply the ideal sample size**.
Also they mention in their statistics some split up by college graduates, though there’s no mention of diverse sample by education level.
UPDATE-19-May-2016: Guardian came out with a new article about what happened.
UPDATE-19-June-2016: As of today, I have a facebook account that’s about 10 days old, and is used as a blog posts distribution tool. (Same for linkedin, they were getting into dark patterns enough that I had to delete and recreate my profile there for clean-up of random community memberships)
* — Or are just clueless.. But given that they seem to be a research firm, they might as well be doing illegal business.
** — One way to calculate this ideal samplesize would be to use a calculator like this.