Tanya Khovanova's Math Blog

Should you try to guess an answer to a multiple-choice problem during a test? How many problems should you try to guess? I will talk about the art of boosting your guessing accuracy in a later essay. Now I would like to discuss whether it makes sense to pick a random answer for a problem at AMC 10.

Let me remind you that each of the 25 problems on the AMC 10 test provides five choices. A correct answer brings you 6 points, a wrong answer 0 points and not answering at all gives you 1.5 points. So guessing makes the expected average per problem to be 1.2 points. That is, on average you lose 0.3 points when guessing. However, if you are lucky, guessing will gain you 4.5 points per problem, and if you are unlucky, it will lose you 1.5 points per problem.

So we see that on average guessing is unprofitable. But there are situations in which you have nothing to lose if you get a smaller score and a lot to gain if you get a better score. Usually the goal of a competitor at AMC 10 is to get to AIME. For that to happen, you need to get 120 points or be in the highest one percentile of all competitors. This rule complicates my calculations. So I decided to simplify it and say that your goal is to get 120 points and then see what mathematical results I can get out of that simplification.

First, suppose you are so accurate that you never make mistakes. If you have solved 20 problems, then your score without guessing is 127.5. If you start guessing and guess wrongly for all of the last five questions, you still have your desired 120 points. In this instance it doesn’t matter whether you guess or not.

Suppose on the other hand that you are still accurate, but less powerful. You have only solved 15 problems, so your score without guessing is 105. Now you must be strategic. Your only chance to get to your goal of 120 points is to guess. Suppose you randomly guess the answers for the 10 problems you didn’t solve. To make it to 120, you need to guess correctly at least five out of the ten remaining problems. The probability of doing so is 3%. Here is a table of your probability of making 120 points if you solve correctly n problems and guess the other problems.

We can see that if you solved a small number of problems, then the probability of getting 120 points is minuscule; but as the number of problems you solved increases, so does the probability of getting 120 points by guessing.

The interesting part is that if you have solved 19 problems, you are guaranteed to get to AIME without guessing. On the other hand, if you start guessing and all your guesses are wrong, you will not pass the 120 mark. The probability of having all six problems wrong is a not insignificant 26%. In conclusion, if you are an accurate solver and want to have 120 points, it is beneficial to guess the remaining problems if you solved fewer than 19 problems. It doesn’t matter much if you solved fewer than 10 problems or more than 19. But you shouldn’t guess if you solved exactly 19.

If you are not 100% accurate things get more complicated and more interesting. To decide about guessing, it is crucial to have a good estimate of how many mistakes you usually make. Let’s say that you usually have two problems wrong per AMC test. Suppose you gave answers to 20 problems at AMC. What’s next? Let us estimate your score. Out of your 20 answers you are expected to get 18*6 points for them plus 5*1.5 points for the problems you didn’t answer. Your expected score is 115.5. You are almost there. You definitely should guess. But does it matter how many questions you are trying to guess?

The correct answer to one question increases your score by 4.5 with probability 0.2, and the wrong answer decreases your score by 1.5 with probability 0.8. One increase by 4.5 is enough for you goal of 120 points. So if you guess one question, with probability 0.2, you get 120 points. If you guess two questions, then your outcome is as follows: you increase your score by 9 points with probability 0.04; you increase your score by 3 points with probability 0.32; and you decrease your score by 3 points with probability 0.64. As you need at least a 4.5 increase in points, it is not enough to guess one question out of two. You actually need to guess correctly on both of them. The probability of this happening is 0.04. It is interesting, but you have a much greater chance to get to your goal if you guess just one question than if you guess two. Overall, here is the table of probabilities to get to 120 points where m is the number of questions you are guessing.

Your best chances are to guess all the remaining questions.

By the end of the test you know how many questions you answered, but you don’t know how many errors you made. The table below tells you what you need in order to get 120 points. Here is how you read the table: The number of problems you solved is in the first column. If you are sure that the number of mistakes is not more than the number in the second column, you can relax as you made at least 120 points. The last column gives the score.

If the number of mistakes you made is one more than in the corresponding row of the table, you should start guessing in order to try to get 120 points. Keep in mind that there is a risk: if you are not sure how many problems you solved already and start guessing, you might ruin your achievement of 120 points.

In the next table I show how many questions you can guess without the risk of going below 120 points. The word “all” means that it is safe to guess all the remaining questions.

You can see that if your goal is to get 120 points, your dividing line is answering 22 questions. If you solved 22 questions or more, there is no risk in guessing. Namely, if you have already achieved more than 120 points, guessing will not take you below that. But if you made more errors than are in the table, then guessing might be beneficial. Hence, you should always guess in this case — you have nothing to lose.

Now I would like to show you my calculations for a situation in which you are close to 120 points and need to determine the optimum number of questions to guess. The first column is the number of answered questions. The second column is the number of mistakes. The third column is your expected score without guessing. The fourth column is the optimum number of questions you should guess. And the last column lists your chances to get 120 points if you guess the number of questions in the fourth column.

You can see that almost always if you are behind your goal, you should try to guess all of the remaining questions, with one exception: if you answered 19 questions and one of them is wrong. In this case you should guess exactly two questions — not all that remain.

Keep in mind that all these calculations are very interesting, but don’t necessarily apply directly to AMC 10, because I simplified assumptions about your goals. It may not be directly applicable, but I hope I have expanded your perspective about how you can use math to help you understand how better to succeed at math tests and how to design your strategy.

I plan to teach you how to guess more profitably, and this skill will also advance your perspective.

Lottery is a tax on people bad at math.

In this article I calculate how bad the lottery is as an investment, using Mega Millions as an example. To play the game, a player pays $1.00 and picks five numbers from 1 to 56 (white balls) and one additional number from 1 to 46 (the Mega Ball number, a yellow ball).

During the drawing, five white balls out of 56 are picked randomly, and, likewise, one yellow ball out of 46 is also picked independently at random. The winnings depend on how many numbers out of the ones that a player picks coincide with the numbers on the balls that have been drawn.

So what is your expected gain if you buy a ticket? We know that only half of the money goes to payouts. Can you conclude that your return is 50%?

The answer is no. The mathematical expectation of every game is different. It depends on the jackpot and the number of players. The more players, the bigger is the probability that the jackpot will be split.

Every Mega Millions playslip has odds printed on the back side. The odds of hitting the jackpot are 1 in 175,711,536. This number is easy to calculate: it is (56 choose 5) times 46.

How much is 175,711,536? Let’s try a comparison. The government estimates that in the US we have 1.3 deaths per 100 million vehicle miles. If you drive one mile to buy a ticket and one mile back, your probability to die is 2.6/100,000,000. The probability of dying in a car accident while you drive one mile to buy a lottery ticket is five times higher than the probability of winning the jackpot.

Suppose you buy 100 tickets twice a week. That is, you spend $10,000 a year. You will need to live for 1,000 years in order to make your chances of winning the jackpot be one out of 10. For all practical purposes, the chance of winning the jackpot are zero.

As the probability of winning the jackpot is zero, we do not need to include it in our estimate of the expected return. If you count all other payouts then you are likely to get back 18 cents for every dollar you invest. You are guaranteed to lose 82% of your money. If you spend $1000 a year on lottery tickets, on average you will lose $820 every year.

If you do not buy a lot of tickets your probability of a big win is close to zero. For example, the probability of winning $250,000 (that is guessing all white balls, and not guessing a yellow ball) by buying one ticket is about 1 in 4 million. The probability of winning $10,000 — the next largest win — is close to 1 in 700,000. If we say that you have no chance at these winnings anyway, then your expected return is even less: it is 10 cents per every dollar you invest.

You might ask what happens if we pool our money together. When a lot of tickets are bought then the probability of winning the jackpot stops being zero. I will write about this topic later. For now this is what I would like you to remember. From every dollar ticket:

• 50 cents goes to the state
• 32 cents towards the jackpot
• 18 cents to other winners

I am not at all trying to persuade you not to buy tickets. Lottery tickets have some entertainment value: they allow you to briefly dream about what you would do with those millions of dollars. But I am trying to persuade you not to buy lottery as an investment and not to put more hope into it than it deserves. If you treat lottery tickets as tickets to a movie that is played in your head, you will never buy more than one ticket at a time.

That is it. I advise you not to buy more than one ticket at a time. One ticket will allow you to dream about the expression on your sister’s face when she sees your new $5,000,000 mansion, but will not destroy your finances.

My recent entry, where I asked you to choose the odd one out among these images

was extremely popular. It was republished all around the world and brought my blog as much traffic in one day as I used to get in a month. Not only did I read the many comments I received, I also followed up on other peoples’ blogs who reprinted my puzzle — at least those that were in either Russian or English. I also got private emails and had many conversations in person about it. The diversity of answers surprised me, so I would like to share them with you.

As I’ve said before, I do not think there is a correct answer to this type of question, but I was disappointed by some of the answers. For example, those who simply said, “The green one is the odd one out,” made me feel that either they hadn’t read the question or hadn’t thought about it very much. It’s a shame that these people spent more time sharing their opinion with the world than thinking about the problem in the first place.

I wouldn’t mind someone arguing that the green one is the odd one out, but in this case an explanation is in order. Many people did offer explanations. Some told me that we perceive the color difference stronger than all other parameters I used, and the green figure pops out of the picture more than anything else. In fact, I personally perceive color difference the strongest among all the parameters, but since there are people who are color blind, I would disregard my feelings for color as being subjective.

You can create a whole research project out of this puzzle. For example, you can run an experiment: Ask the question, but flash the images above very fast, so there is no time for analysis — only time to guess. This allows us to check which figure is the first one that people perceive as different. Or you can vary the width of the frame and see how the perception changes.

Color was not the only parameter among those I chose — shape, color, size and the existence of a frame — that people thought was more prominent. My readers weighed these parameters unequally, so each argued the primary importance of the parameter they most emphasized. For example, one of my friends argued that:

The second figure should be the odd one out as, first, it is the only one without a frame, and, second, it is the only one comprised of one color rather than two. So it differs by two features, as others differ only by one feature.

A figure having one color is the consequence of not having a frame, so this particular friend of mine inflated the importance of not having a frame.

However, I can interpret any feature as two features. For example, I can say that the circle is the odd one out because not only is it a different figure, but it also doesn’t have any angles. Similarly, the last one is the smallest one and the border width is in a different proportion to its diameter.

On a lighter side, there were many funny answers to the puzzle:

• The one that says I am special.
• The right one because it is right.
• The fourth one, because four is the only composite index.
• The one that says I am not special.

For the which-is-the-odd-one-out questions, the designer of the question is usually expecting a particular answer. So here’s the answer I expected:

There is only one green figure. Wait a minute, there is only one circle. Hmm, there is only one without a frame and there’s only one small figure. I see! The first one is the only figure that is not the odd one, that doesn’t have a special property, so the first must be the odd one out. This is cool!

And the majority of the answers were exactly as I expected.

Since this is a philosophical problem, some of the responses took it to a different level. One interesting answer went like this:

All right, the last four figures have special features; the first figure is special because it is normal. Hence, every figure is special and there are no odd ones here.

I like this answer as the author of it equated regular features with a meta-feature, and it is a valid choice. This answer prompted me to write another blog entry with a picture where I purposefully tried to not have an odd one out:

Though I wrote that the purpose of this second set of images is to show an example where there is no odd one out, my commentators still argued about which one was the odd one out here.

Finally, I would like to quote Will’s comment to my first set of images:

The prevailing opinion is that the first is least unique and is therefore the oddest. But it is the mean and the others are one deviation from it. Can the mean be the statistical anomaly?

And Cedric replied to Will:

Yes, I think the mean can be a statistical anomaly. The average person has roughly one testicle and one ovary. But a person with these characteristics would certainly be an anomaly.

An ancient Russian joke:

Patient: Doctor, is there a medicine I can use to prevent my girlfriends from become pregnant?
Doctor: Kefir.
Patient: Should I drink it before or after sex?
Doctor: Instead of.

I have a more pleasurable suggestion than drinking kefir: date postmenopausal women. There are many other reasons why men enjoy dating older women, but since my blog is about mathematics, I would like to dig into some relevant numbers.

We know that boys are born more often than girls, and men die earlier than women. Somewhere around age 30 the proportion in population switches from more boys to more girls. And it gets more skewed with age. So there’s a deficit of older men. In addition, a big part of the population is married, making the disproportions in singles group more pronounced. So I decided to look at the numbers to see how misshaped the dating scene is.

This 2008 data comes from the U.S. government census website’s table “Marital Status of the Population by Sex and Age: 2008. (Numbers in thousands. Civilian non-institutionalized population.)” To calculate the number of singles, I summed up the widowed, divorced and never married columns.

These data alone cannot explain the dating situation. For example, I have no way of knowing what proportion of each gender isn’t interested in dating the opposite sex, or even in dating altogether. But the trend is quite clear: the proportion of men in younger categories is much higher. That implies that there is less competition for older women. So those young men who are open to dating much older women might have more options and those options might be more interesting.

I just turned 50 and plan to return to dating again. Looking at the data I see that there are 11 million single men older than me and 34 million who are younger than me. If I were to pick a single man randomly, I am three times more likely to end up with a younger man.

Supposedly we live in a free society, where people can do what they want as long as they do not harm anyone else. Still our society often disapproves of women dating much younger men. Consider this definition from Wikipedia:

“Cougar — a woman over 40 who sexually pursues a much younger men.”

This derogatory term portrays such women as predatory. Not only is there nothing wrong with women dating younger men, but it makes no sense for older women to ignore the imbalance of the dating scene and be closed to relationships with much younger men. After all, the demographics are also affected by the fact that women live longer, probably because of their healthy life style, non-risky behavior and positive attitude to life.

Can someone explain to me again why sane, healthy, non-risky women with positive attitudes to life are called “cougars”?

I recently read an article titled “Think having children will make you happy?” that discusses studies correlating happiness and having children. Some studies show that parents and non-parents have the same level of happiness. But other studies show that non-parents are happier. So, do children make us less happy?

There are two major reasons that kids might make people less happy in a long run. First, children require a lot of resources; they put a strain on our budget, time and careers. As my friend Sue Katz puts it: parental unhappiness could stem from poverty, illness, fighting the educational institutions, feeling stuck in a violent relationship because of the kids — a million things, depending on class and options.

Second, children might not live up to our expectations. Parents often dream that their children will have wonderful careers, be supportive of their parents later in life and most importantly be good people. But in reality, children choose their own careers, not necessarily a path approved by their parents. Plus they might live at a distance or the relationship might be strained. They might even develop completely different values from their parents.

The article claims that on average kids will bring more problems than joy to our lives. Do not rush to cancel unprotected sex with your spouse tonight yet.

My friend Peggy Boning suggested that the study should have separately checked parents who wanted children and parents who didn’t. It could be that parents who didn’t want children are less happy than parents who wanted them. Which means that if you do not want children, make sure you have protected sex. If you do want children, you might be happier with children than without.

Anyone who has studied statistics knows that correlation doesn’t mean causality. An individual who wants to have children might be happier as a result, and at the same time the statistics data may well be true. I’d like to find arguments that can make peace between these two suppositions.

• Younger people are more often childless than older people. If studies do not differentiate by age and younger people are generally happier than older people, than we might see parents less happy, because they are older on average.
• I am sure that suicidal people are more likely to actually kill themselves if no one depends on them. Thus, the most unhappy segment of childless people will have died out, while unhappy people with children will drag on.
• Some very happy people might be self-centered and do not want children.

Feel free to add your own ideas.

A new study is out. Dr. Satoshi Kanazawa blogged about his new discovery. He claims that he can explain why many studies show that men have higher intelligence than women. In his posting Why men are more intelligent than women he posits that intelligence is correlated with height. Taller men on average are smarter than shorter men.

He also claims that given the same height, women are more intelligent than men. As he puts it: “Women who are 5’10” are on average more intelligent than men who are 5’10”.” According to him the only problem women have in the brains department is that they aren’t tall enough.

I couldn’t find the study itself, only his own announcement. My problem with his study is that, according to Dr. Kanazawa’s description, he used data from the National Longitudinal Study of Adolescent Health. If we are talking about adolescents we need to take into account that children grow taller and smarter with age. So any difference in intelligence among the kids of different heights may easily be explained by age. Taller boys may be older and therefore likely to perform better on intelligence tests.

As to intelligence differences between boys and girls of the same height, these girls who are 5’10” may be from higher grades than boys who are 5’10”.

Some IQ tests are designed to take age into account, but what’s totally weird is that a scientist is studying the correlation of intelligence and height, using a population that is in the middle of a physical and mental growth spurt.

As a mathematician, I’ve been around many people of great intelligence, but I’ve never perceived bright people as especially tall.

Here is the picture of the USAMO winners for 2007. These are certainly extremely smart kids and I know their heights. The sixth student on the left is my son, Sergei. I personally met all these kids and compared to their peers they are not — except for one boy — especially tall.

I wanted to see how different presidents affected the Dow Jones index. The index was invented at the end of the nineteenth century, so for my convenience, I will start my analysis from the beginning of the twentieth century. I skipped the presidents who were in office for only four years — four years might not be enough to rebuild a bad economy or to destroy a good one. Besides, in order to give the presidents a fair chance, I compared them for the same time period: eight years.

So I removed from my consideration all those who only served for four years: William Howard Taft, Herbert Hoover, Jimmy Carter and George H.W. Bush. I also combined two presidents together, when one succeeded the other mid-term for a total of eight years. Namely, I combined Warren Harding with Calvin Coolidge, John Kennedy with Lyndon Johnson, and Richard Nixon with Gerald Ford. For Franklin Roosevelt, I only considered the first eight years of his presidency.

Please note that it was not always precisely eight years — the inauguration date was sometimes moved. So Theodore Roosevelt and Harry Truman had slightly less than eight years. I tried to use the Dow Jones index from the exact day of each inauguration, but not all the dates were available in the file I used. So sometimes I had to pick the previous day.

Some might argue that I need to scale the Dow Jones Index. For example, the inflation rate was very different for different presidents. It is generally accepted that the value of one point in the Dow Jones Index decreases with time, but inflation is only one of many elements contributing to that change. Nonetheless, I took a look at that and the resulting picture didn’t change much anyway when I adjusted for inflation.

The Dow Jones is just one number. An increase in the Dow Jones does not completely describe the state of the economy, but it is certainly an interesting measure in its own right.

Let’s look at how the presidents and the presidential teams performed, sorting them from best to worst:

When I started this calculation I expected Clinton to be doing well and Bush badly, I just didn’t know exactly how good/bad they were. But the most interesting result of this exercise is the fact that the highest increase in DJI happened right before the Great Depression.

What can I say? I should have done this analysis eight years ago. Maybe the proximity of Clinton’s performance to the pre-depression boom could have urged me to move my 401(k) from stocks. Sigh.

Recently I conducted an experiment. I wrote an essay “What’s Hidden?” in which I claimed that the essay had a hidden secret message in it. I coded the message using a very simple method — to read it you need to combine together all the capital letters in the essay.

The goal of the experiment was to audit intelligence agencies of different countries. I wanted to check if this essay would draw any special attention.

Intelligence agencies should crawl around the web and check places that might have secret messages. They might also want to sieve Internet data through some standard coding techniques and check if there are coded messages out there. But the Internet is so vast that most agencies might not have the resources to parse through all the web pages. They probably only analyze suspected pages.

Anyway, I wanted to see if my traffic for this essay would be different from the usual. I have a tool for that — Google Analytics, which provides aggregated geographical data of my traffic. Looking at the results I can see that the visits to this particular essay were mostly from the United States, with a few from Europe. The total number of visits was small, especially compared to my essay on masturbation.

If an intelligence agency has any intelligence it should hide its visits from Google Analytics and crawl around the web without being registered. For example, they can use cached Google pages.

So my intention in this experiment was to check for any agency that had so much time and money on their hands that they were monitoring the entire web and, at the same time, was dumb enough to leave a trail. I am happy to conclude that there is no such agency, with only one potential exception: my home country — the United States.

Teacher: Why didn’t you do your statistics homework?
Student: I read a statistical study that the students who spend more time on their homework get lower grades.
Teacher: So you didn’t do your homework in order to increase your grades?
Student: Yep.
Teacher: I have been teaching you that correlation doesn’t mean causality. Did it ever occur to you that students with good grades already know some of the material and they do not need much time to complete their homework?
Student: Oh?
Teacher: You are getting an F for not doing your homework. Now you might understand causality better.

When I came to the US, I heard about Mensa — the high IQ society. My IQ had never been tested, so I was curious. I was told that there was a special IQ test for non-English speakers and that my fresh immigrant status and lack of English knowledge was not a problem. I signed up.

There were two tests. One test had many rows of small pictures, and I had to choose the odd one out in each row. That was awful. The test was English-free, but it wasn’t culture-free. I couldn’t identify some of the pictures at all. We didn’t have such things in Russia. I remember staring at a row of tools that could as easily have been from a kitchen utensil drawer as from a garage tool box. I didn’t have a clue what they were.

But the biggest problem was that the idea of crossing the odd object out seems very strange to me in general. What is the odd object out in this list?

Cow, hen, pig, sheep.

The standard answer is supposed to be hen, as it is the only bird. But that is not the only possible correct answer. For example, pig is the only one whose meat is not kosher. And, look, sheep has five letters while the rest have three.

Thus creative people get fewer points. That means, IQ tests actually measure how standard and narrow your mind is.

The second test asked me to continue patterns. Each page had a three-by-three square of geometric objects. The bottom right corner square, however, was empty. I had to decide how to continue the pattern already established by the other eight squares by choosing from a set of objects they provided.

This test is similar to continuing a sequence. How would you continue the sequence 1,2,3,4,5,6,7,8,9? The online database of integer sequences has 1479 different sequences containing this pattern. The next number might be:

• 10, if this is the sequence of natural numbers;
• 1, if this is the sequence of the digital sums of natural numbers;
• 11, if this the sequence of palindromes;
• 0, if this is the sequence of digital products of natural numbers;
• 13, if this is the sequence of numbers such that 2 to their powers doesn’t contain 0;
• 153, if this is the sequence of numbers that are sums of fixed powers of their digits;
• 22, if this is the sequence of numbers for which the sum of digits equals the product of digits; or
• any number you want.

Usually when you are asked to continue a pattern the assumption is that you are supposed to choose the simplest way. But sometimes it is difficult to decide what the testers think the simplest way is. Can you replace the question mark with a number in the following sequence: 31, ?, 31, 30, 31, 30, 31, … You might say that the answer is 30 as the numbers alternate; or, you might say that the answer is 28 as these are the days of the month.

Towards the end of my IQ test, the patterns were becoming more and more complicated. I could have supplied several ways to continue the pattern, but my problem was that I wasn’t sure which one was considered the simplest.

When I received my results, I barely made it to Mensa. I am glad that I am a member of the society of people who value their brains. But it bugs me that I might not have been creative enough to fail their test.