The ‘I will not be a stereotype’ stereotype

We all strive to be unique. But we want to be one of the guys. Therein lies most of the stress in life. Trying to fit in while hoping to stand out makes huge demands on our psyches. Belonging to something provides us safety—a soft blanket if you will, to shield us from harsh oblivion. Soon, the blanket turns into a cocoon we thrash against, trying to shine amidst the tapestry we so desperately wove ourselves into.

You know, for a Gujju guy, he doesn’t wear a whole lot of cologne. He’s fair for a Madrasi. Hey I may be Marwadi, but I spend money like it’s going out of style. She’s Punjabi but she won’t get married at 23. I’m Indian but I tip well. He dances well, you know, for a white dude. Or there goes a black guy with a stable job.

Stereotypes have a grain of truth to them. There are traces of cologne in the air in Ghatkopar well after the wearers have left for New Jersey and a lot of Madrasis are dark-complexioned and wear pants that show way too much ankle for a morning class at IIT. More pennies have been pinched by Marwadis than stewardesses by Warne, and plenty of Punjabi girls are sealed, labeled, and shipped off into matrimony by 23. Most desis would cough up a gall bladder before leaving an acceptable tip at the Olive Garden on a special night. And Caucasian rhythm disorder has been talked about to death. We are all clichés, bundled in statistical noise. As much as it hurts, we are all cookie-cutter.

James Russell Lowell — ‘Whatever you may be sure of, be sure of this, that you are dreadfully like other people.’

But not me right? I’m different; it’s obvious that I stand out. I speak so well—at least it sounds great in my head. And I don’t drive a Toyota like the other desis. I may live in New Jersey, but not by choice. I am South-Indian but I’m lighter, and yes, I occasionally pronounce khaana as kaana, but I cover it up quickly and move on like the smooth operator I am. And I drank Jack Daniels, not Royal Stag, before I started drinking single malt, not Jack Daniels. Even the most thorough meta analysis of how we analyze ourselves doesn’t protect us from thinking there’s something really special inside us. Why did we evolve this delusion? Growing up, whenever I scored average grades, mom wanted me to do better cause I was worth better, according to her. Solid unbiased evaluation there, ma. Who can blame her? We are all Keanu Reeves waiting for a big black guy in ‘what if I told you’ glasses to tell us we are the one and that gravity is just a guideline. So we need to set ourselves apart for the second coming of our personalities.

But non-conformism is a 24-hr job, and it’s thankless and self-defeating because the harder you try to not conform, the more stereotypical you become. Pretty soon, you’re the one watching social trends just so you know what to scoff at. So people dumpster dive into the early songs of popular musicians, or that short film made ten years ago by today’s Oscar-winning director, just to lord their refinement over the lemmings being swept by the zeitgeist. We out-gourmet each other by waiting in endless queues for cronuts and laugh at those shopping at Whole Foods as wanna-be yuppies, all because we buy our quinoa directly from the source at the extemporaneous market that sets up every time the house tries to repeal Obamacare.

In today’s politically correct world, where self esteem is the most endangered species, it seems imperative to tell the newest entrants that they are pretty little snowflakes and each one is endowed with something special that the world will eventually recognize. While it’s true for some—the brainiacs, the athletes, the hunks & babes—for most people, all that awaits you is the realization that you’re hopelessly mediocre with a few sprinkles of accidental genius that might, if you’re lucky, be noticed.

And so, failing to be unique by design, we strive to be unique in our choices. Even in the most pointless ones.

Keep the change. Just keep everything.

Tipping irks me.

I admit, no dollar leaves my wallet without my full-throated resentment, but my hatred of tipping goes beyond that. It’s not a question of percentage or quality of service; I’m annoyed that a decision that’s supposedly left up to me comes with strings attached. Tip well or get some saliva in your soup. Tip too well, and you’re the chump who got mugged at the Olive Garden.

And yet, I’m a decent tipper. Never under 15%, and I’ve occasionally gone up to 25%. And then there was that calculation error that caused me to leave a 33% tip, and a shocked waiter probably. Perhaps it’s the pressure of the social contract living in the USA or that I just like to keep visiting my favorite restaurants. Or, who knows, I might be fighting some imaginary Indian-lousy-tipper stereotype. I remember tipping in India to be brutal: people rounded off 49s to 50 and 99s to 100. Tipping was just a convenience to avoid additional math. And then I came to New York City, where we tip cab drivers we’ll never see again for not getting us killed. We tip baggage handlers at the airport so our checked-in bags follow our itinerary. If I were to visit as many countries as my bags have, I’d be wearing a beret-turban-sombrero.

Even if the original idea of tipping was to provide us some control over how we reward our servers and perhaps as an incentive to them to treat us well, I doubt it serves that purpose. Even if our tips rose and fell with how well we are treated at various places of business, no two customers would agree on a definition of exceptional service. So, using tips to fix service is at best a dream.

“But Bharat, waiters are paid much less than minimum wage, and the government assumes they’re getting tipped while taxing them.”

It bothers me that waiters aren’t paid a living wage only to the extent that their rent is somehow my responsibility. I hate the idea of forcing restaurants to pay their servers more. But other types of business owners are under the governmental hammer for wages, and even health insurance. Yet, for some reason, making sure this poor bastard affords his annual physical is somehow my responsibility. I don’t mean to go all Mr. Pink on you, but tipping is  neither scientific nor fair. Female waitresses get tipped more than male ones, and being large-breasted and blonde makes those dollars flow more than all the free dessert in the world. So most customers aren’t rewarding the prompt service of the nice lady at Applebees; they’re just signaling with their wallet their appreciation for narrow waists.

And the stress, oh my god the stress. How much is enough? Am I being cheap? What if I’m overtipping? What if I’m setting a new baseline and the next average tip appears small? Frankly, I prefer restaurants that levy a constant service charge and exempt me from the mental calisthenics of balancing privileged guilt against a thick wallet on a full stomach. When a meal is done and I’m working up the social decency to resist loosening my belt in public, the last thing I need is to worry about is putting my waitress’ kids through college. With the service charge, I know beforehand that everything I see on the menu is going to cost a fixed percentage more, and I can decide whether I want it or not.

When it comes to tipping, I think at least some people make rules up as they go along. There’s this one-upmanship of out-tipping the other guy so you come out looking like the big shot. Tipping bartenders five bucks for pouring beer into a glass with minimal spillage is a little silly; sure, it’s a good way to ensure you never have to wait for a drink in a crowded bar maybe, but at an academic social?

But I guess someone should make up for those sickos who leave these:

It's a good thing these people believe in hell

It’s a good thing these people believe in hell

How much dice does god play?

I’ve always wondered why high schools bury students in calculus instead of teaching them the beauty of statistics and probability. A tiny fraction of these students will actually use calculus in their lives, but statistics are for everyone. And without clear statistical principles in our head, we get intimidated by numbers. I thought a small write-up on probability and statistics that touches upon some of their arcane concepts without sounding too technical was in order.

 Randomized response

To reel you guys in, let me begin with a real world application of probability, nothing obscure. Just an interesting use for the concept.

Suppose you’re conducting a survey where you ask people whether they cheated on their spouse. In spite of repeated assurances of confidentiality, the participants could never be sure that their data wouldn’t be traced back to them. After all, it’s on a piece of paper or a file on some computer. Who’s to say some disgruntled employee wouldn’t release them to the world?

The randomized response method, that’s who. It allows us to obtain our data without causing a rip tide of punitive alimonies. Here’s how it goes. When the participant comes to a yes/no question about a sensitive issue, he flips a coin. If the coin comes up heads, he fills Yes. If it comes up tails, he answers truthfully. It’s that simple. No one watches him flip the coin, so his motivations for filling Yes are secret.

We know that if we flip a coin enough times, we’ll get heads roughly half the time. So let’s say 1000 people participated in the survey, and assume that 700 of them answered Yes to the damning question. And 300 answered No. There is only one reason to answer No—you didn’t cheat on your spouse. This means every person who answered No got tails on the coin flip. That means an equal number of people must have gotten heads (300). So, out of the 700 who answered Yes, 300 did so because of the coin flip, which leaves 400 people who definitely cheated—their spouses are none the wiser.

Bayes’ theorem

Thomas Bayes blew our minds on conditional probability, you know, those icky questions like, “If it rains tomorrow, what’s the probability that the bus will be late?” The Bayes theorem, if one’s unfamiliar with it, gives us some counter-intuitive answers to questions that we would otherwise take for granted.

Say 1% of women over forty have breast cancer. Assume that 95% of women with breast cancer will test positive for it. Also assume that 5% of those without breast cancer will also test positive—false alarms. If a woman tests positive, what’s the probability that she actually has breast cancer? 95%? 90%? It’s at least 50%, right? It’s actually about 16%, which, incidentally is the percentage of doctors who got this question right.

Whenever an event we test for is present in a small fraction of the population, however precise the test, any true positive will be drowned in the absolute number of false alarms. Welcome to the world of Bayesian probability. Simply put, if 10000 women were tested for breast cancer, and 100 of them actually have it, 95 of the 100 will test positive. And out of the 9900 who don’t have breast cancer, 5% or 495 will test positive. This means, for every 10000 tested, 590 will test positive, of which only 95 will actually have breast cancer—16%.

This is why doctors re-test the samples that test positive. In this case, if a sample tests positive twice, the probability of cancer rises to 78%. Fun, right?

Confidence limits and statistical significance

Whenever those of us in the science fields hear the word significant, we go, “Oh yeah? Prove it.” When we say ‘significant’ we mean statistically significant with a given probability value. Even those outside the sciences hear of confidence limits and statements like “We know this with 95% confidence…” So what does it mean to have statistically significant information or to have confidence in it?

If we conclude something from a study with 95% confidence, we mean that we allow for a 5% chance that our results were sheer dumb luck. In other words, even though scientific research follows an innocent until proven guilty principle, if we kill 5 out of every 100 innocent people, we call it a good day.

To elucidate this, let’s say I gave you a coin and told you that it favors heads, i.e. if flipped enough times, it will give more heads than tails. It’s up to you, the skeptic, to test it instead of just believing me.

So you flip the coin once and get heads. Eureka! This coin favors heads! Not so fast…there was a 50% chance of getting heads by pure chance anyway. At best, you can state with 50% confidence that this coin favors heads. So you ante up again and re-flip this coin. Another heads. Don’t call Stockholm just yet. There’s now a 50% of 50% i.e. 25% probability that these two results were pure chance. But your confidence has increased now. You can state with 75% surety that there’s some funny business with the coin.

You flip it again. Another heads. Now your confidence has gone up to 88%.

Flip again. Another heads? You’re now 94% confident that the coin is biased. With the next flip, your confidence rises to 97%, which is more than enough for most scientific experiments.

Of course, I give this example to explain the intuition behind the % confidence concept. This experiment takes for granted a lot of things that change with every flip—how high you flip, air resistance, which side faces up when you flip, etc. In reality, you don’t accuse a coin of bias after five flips.

Expectation, Law of large numbers, and the Gambler’s Fallacy

Consider an unbiased six-faced die with the faces numbered 1 through 6. If you roll a 1, you get $1 and if you roll a 2, you get $2…you get the idea. We all know that the probability of landing any particular number is 1/6. If you threw enough times, what’s the average amount of money you’d make per roll?

Expectation simply means the probability of an event multiplied by the reward or punishment associated with that event. There’s a one-in-six chance of rolling any given number.

The law of large numbers says that if you roll this die enough times, your expectation per roll winds up around $3.5. Every number is equally likely, so the reward expected from any particular roll is the average of the rewards for each number—

(1/6 X 1) + (1/6 X 2) + (1/6 X 3) + (1/6 X 4) + (1/6 X 5) + (1/6 X 6)

= (1+2+3+4+5+6)/6

= 21/6 or $3.5

We must remember that this averaging out happens over many many rolls…nearly approaching infinity. If we ignore this, we commit what’s known as the gambler’s fallacy. Every number on the die is equally likely, and each roll is independent of any other. If you rolled 1, 2, and 3 in succession, it doesn’t mean that 4, 5, and 6 are due. Every roll has 1/6 likelihood of yielding a particular number. Yes, if you rolled the die 60000 times, you’ll most likely end up with equal rolls for each number.

People who buy lottery tickets based on numbers that are due are fooling themselves. Then again, people who expect to make a lot of money on lottery tickets wouldn’t be swayed by statistics and probability anyway.

So there it is. A small primer on statistics and probability with some real-world examples. Some of this is oversimplified here and more nuanced in actuality. Some of the intuitive explanations are based on how I understand them and subject to further exposition.

Related articles

Connecticut, gun-control, and human nature

LAWS are written for the average citizen, the meaty portion of the demographic bell curve, but a referendum on a law usually springs from something an outlier does. It may be subtle, like someone exploiting a tax-loophole, or in-your-face, like someone walking from classroom to classroom firing multiple rounds at cherubic victims.

Adam Lanza (Wikipedia)

Adam Lanza discharged a firearm on innocent children, teachers, and his mother, before killing himself. Twenty eight people died, fourteen of them children. We have seen this before. The Virginia Tech shooting happened about five years ago. And a few months later—not nearly as gruesome, but closer to home—a man had sneaked a gun into my university campus before he was apprehended. Luckily there were no casualties. These, with the Gabrielle Giffords case,  and the Aurora shooting, have ensured a stalemated gun-control debate, with one side claiming it’s too soon to talk about it and the other questioning the logic of civilians carrying assault weapons. What we have here is a nation divided, with most participants refusing to budge, on an issue that isn’t elucidated as much as we’d like to believe.

For every gun-owner who kills innocent people, there are thousands who don’t. That we cannot ignore. Instead of restricting the sale of weapons, let’s collect and publicize information on gun-owners. Nancy Lanza was a survivalist who owned over a dozen guns and stockpiled food in preparation for the ‘apocalypse.’ She also took her sons to shooting practice. There are fewer red flags at a communist rally. Instead of banning assault weapons for civilians, why not use the information? Put someone such as Lanza’s mother on a watch-list. When a twenty-year old has access to and carries semiautomatics, in violation of Connecticut law, follow him around in a chopper if you like. The Second Amendment prohibits none of that.

The more regulatory hoops people have to jump through to get whatever they want, the likelier that they pursue illegal methods to get it. And shadow economies that fly under the radar use violence as currency. The drug war and Prohibition have taught us that. Let people buy the weapons legally, but keep tabs on them. Educate them that the Second Amendment doesn’t protect them from a tyrannical federal government that possesses nuclear weapons. Nothing does. It was drafted back when the government and the people had the same weapons. Today, you have the right to own a gun, not the right to keep it secret. It’s not a perfect solution, but it’s something.

Some say that had twenty-eight people died in a terrorist attack, the people drooling all over the Second Amendment right now would have gladly forfeited what’s left of their Fourth Amendment. That, I believe, is a false equivalence. Terrorists are malevolent but sane people who kill in cold blood. Every single terrorist act must be punished swiftly and harshly, or more will happen. But this man was crazy, and besides his mother, he didn’t know his victims; so this wasn’t personal.

It is a natural human tendency to take for granted the good things that happen and to regard as the workings of the devil the bad things. And that if a bad thing comes along, you say, my God, we ought to pass a law and do something. — Milton Friedman

Gun ownership prevents crimes too. Sure, fewer guns are fired in defense than offense, but the presence of a gun, or even the possibility of one, makes a person less of a sitting duck. We cannot know of all the attempted burglaries, rapes, and muggings thwarted by the victim’s possession of a gun, without even firing it. While this argument does not justify a 20-year-old carrying a Bushmaster XM-15, it does muddy the issue.

It’s human nature to make sense of tribulation—a significance, anything to escape the sad truth that we are but dots on a tapestry, whole lives without meaning to anyone except those living them. (Perhaps that’s why our ancestors invented religion.) I don’t mean to insult the loss of life, or those that died. But these events are an aberration. It’s unlikely and unfortunate when an earthquake or a tsunami occurs, and similarly, now and then someone, somewhere snaps and hurts people without reason. This wasn’t an act of terrorism, not a murder for profit, nor anything preventable. This was a tragedy. Let’s grieve with all of our hearts and comfort the bereaved.


Let’s not forget, in our sorrow for the victims and our indignation on guns, that there were heroes in that school. It is often said that heroes are those who put themselves in harm’s way. The teachers and aides, the principal, and the school psychologist showed outstanding courage as they selflessly rescued as many children as they could, often paying with their own lives. Victoria Soto actually misdirected Lanza by telling him that her students were in the auditorium, while she hid them in cabinets and cupboards. She probably knew he’d kill her, but she protected the tots in her charge anyway. These women did more than save lives. They did wonders to conserve my faith in humanity. And probably yours.


A short-story I wrote in dialogue form four years ago. The sentences in Hindi are translated in parentheses.

Originally posted on Bharatwrites:

“Hey man…can you come over in an hour?”
“Ya sure…what’s up?”
“Aa jana phir batata hoon.” (I’ll tell you when you get here.)
“Okay, see you in an hour.”
“Accha sun, quarter leke aana.” (Bring a quarter liter of whiskey)
“Sure…Royal Stag?”
“Abbe kanjoos, abhi to note chaapne laga hai…bring JD at least!” (Cheapo! You’re making good money now. At least bring a Jack Daniels.)
Forty five minutes later…
“Early as usual!”
“Well, quarter ghar mein padi thi (I had some whiskey at home)…and traffic was low…”
“So, you came via Panch Pakhadi?”
“Yeah, but with a few unorthodox detours on the bike, I managed to avoid traffic…now tell me”
“Arre…let me make a small one first…soda for you?”
“Make mine with Coke, by the way, go slow, I brought only one quarter…”
Arre mera to on the rocks hone wala hai (dude, mine’s gonna be…

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