Poll
| 25 votes (49.01%) | ||
| 16 votes (31.37%) | ||
| 7 votes (13.72%) | ||
| 4 votes (7.84%) | ||
| 12 votes (23.52%) | ||
| 3 votes (5.88%) | ||
| 6 votes (11.76%) | ||
| 5 votes (9.8%) | ||
| 12 votes (23.52%) | ||
| 10 votes (19.6%) |
51 members have voted
DisagreeQuote: ThatDonGuy
I'll go with the obvious answer: I expect him to be on the sidewalk.
Since the sidewalk runs north-south, the distance from the sidewalk will be the difference between the number of steps east and the number of steps west. However, since these are equally likely with each step, the expected number of steps east equals the expected number of steps west.
For that matter, since the expected number of steps north equals the number of steps south, I expect him to be at his starting location.
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The answer is (10,000/π)^.5 =~ 56.419 steps from the sidewalk. That’s technically an approximation though a very accurate one. The formula comes from integrating the normal curve times x from zero to infinity then multiplying times two. This gives the expected distance from the mean.Quote: Ace2Here’s another easy one:
A drunkard starts walking on a straight sidewalk that runs north-south. His goal is to walk northward, but for each step he’s equally likely to go one foot directly north, south, east or west.
After 10,000 steps, how far off the sidewalk would you expect him to be?
Closed form solutions only.
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The exact answer (shown to ten digits) of 56.41825312 can be obtained via Markov chain, though that’s not a closed form solution.
If you were to start searching for the drunkard, the best place to start would be at the sidewalk since you don’t know which side of it he’s on, but you’d be an average of ~56 steps away from it when you found him. The chance of him being on the sidewalk is <1%
Quote: Ace2The answer is (10,000/π)^.5 =~ 56.419 steps from the sidewalk. That’s technically an approximation though a very accurate one. The formula comes from integrating the normal curve times x from zero to infinity then multiplying times two. This gives the expected distance from the mean.
The exact answer (shown to ten digits) of 56.41825312 can be obtained via Markov chain, though that’s not a closed form solution.
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Technically, an approximation isn't one either.
The closest to a "closed form solution" that I got was this:
Each step has probability 1/4 of adding 1 to the number of steps to the left of the sidewalk, 1/4 of subtracting 1, and 1/2 of keeping it the same.
Let (m, n, 10,000 - (m + n)) represent the number of steps to the left, the number to the right, and the number forward/backward, with each one being >= 0 and <= 10,000.
The number of steps away from the sidewalk is |m - n|, and the probability of that particular triple is C(10,000, m) C(10,000 - m, n) (1/4)^10,000, or C(10,000, m) C(10,000 - m, n) / 2^20,000.
The solution is the sum over all m from 0 to 10,000 of (the sum over all n from 0 to (10,000 - n) of ( |m - n| C(10,000, m) C(10,000 - m, n) ) ), divided by 2^20,000.
However, I could not find a way to simplify that.
-62-36
Quote: WizardI get a lot of simple math problems on my Facebook feed. Usually there is a strong consensus on the answer, but this one is split about 50/50.
-62-36-72
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My answer would be:
- 6² - 36
= - (6 * 6)-36
= - 36 - 36
= - 72
An alternate solution using brackets is:
(-6 * -6) - 36
= 0
Quote: WizardI get a lot of simple math problems on my Facebook feed. Usually there is a strong consensus on the answer, but this one is split about 50/50.
-62-36-72
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Quote: WizardI get a lot of simple math problems on my Facebook feed. Usually there is a strong consensus on the answer, but this one is split about 50/50.
-62-36-72
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Wizard is correct

Thus, state the convention you are using to decide whether exponentiation or unary minus has precedence.
Dog Hand
(-6)^2 (-36) = -1,296
I don’t agree with that answer but one could make the argument if parentheses can be implied
Quote: Ace2If parentheses are implied around the -6 to get (-6)^2 - 36 =0, then we should be consistent and assume parentheses are implied around the -36. Therefore:
(-6)^2 (-36) = -1,296
I don’t agree with that answer but one could make the argument if parentheses can be implied
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Except that, since that minus sign is between two numbers, it is not unary, but binary.
Quote: Ace2Are you saying “unary” -6 is not the same as “binary” 0 - 6 ?
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Not at all.
However, I am saying that 0 - 6 = -6, and not 0 - 6 = (0)(-6) = 0.
Quote: Ace2Using a random number generator, you pick a number (x) between zero and one. You then apply the formula x^(x^2) = y. What x value will give the lowest value of y?
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We are asked to find the minimum of y = x^(x^2) where 0 <= x <= 1.
dy = d(x^(x^2))
= d(e^(x^2 ln x))
= e^(x^2 ln x) d(x^2 ln x)
= x^(x^2) (x + 2x ln x) dx
This = 0 when 2x ln x = -x, so ln x = -1/2, and x = e^(-1/2) = 1 / the square root of e, or about 0.60653
For some reason I was surprised to find an e in that one
Quote: Ace2Agree.
For some reason I was surprised to find an e in that one
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e shows up a lot with exponentiation, since the first derivative of a^x is (a^x ln a) dx.
Bonus problem:
Prove that x^(x^2)) approaches 1 as x approaches 0 from the positive side
Quote: Ace2Any positive number raised to the exponent of zero equals one. So as (x^2) approaches zero, x^(x^2) approaches one
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Not passing the smell test. As x^2 approaches 0, x^(x^2) approaches 0^0.
x^(x^2)) = e^(ln (x^(x^2))
= e^(x^2 ln x)
Since e^x is strictly increasing, the limit of e^(x^2 ln x) = e^(the limit of x^2 ln x)
= e^(the limit of ln x / x^(-2))
Using L'Hopital's rule, this is e^(the limit of x^(-1) / ((-2) x^(-3)))
= e^(the limit of -x^2 / 2)
Since x is approaching 0, this approaches e^(-0/2) = 1.
As a simple example consider 1+1/2+1/4... which tends to 2. If you give me a delta of say 1/500, then I can show the total of 1+1/2+1/4...+1/512 is within 1/500 of 2. If you give me a smaller delta, then I just keep on going until I reach a small enough fraction.
Exactly. Since 0^0 = 1, it confirms the aforementioned proof. Additionally, the exponent of x^2 will always be less than the base of x for any value of 0<x<1, so the function gets closer to 1 as x approaches zeroQuote: ThatDonGuyAs x^2 approaches 0, x^(x^2) approaches 0^0.
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Quote: Ace2Exactly. Since 0^0 = 1, it confirms the aforementioned proof. Additionally, the exponent of x^2 will always be less than the base of x for any value of 0<x<1, so the function gets closer to 1 as x approaches zeroQuote: ThatDonGuyAs x^2 approaches 0, x^(x^2) approaches 0^0.
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Excuse me? 0^0 = 1?
Would you agree that, for example, combin(5,0) = 1?
Regardless, we are evaluating the function as x approaches zero, not at x equals zero
What size bankroll should you bring to give yourself a 1/3 chance of busting, 1/3 chance of doubling and 1/3 chance of finishing the 1200 hands without busting or doubling?
Assume a standard deviation of 1.1547, flat betting $500 one hand at a time and perfect basic strategy to realize the 0% edge
Quote: Ace2You go to Vegas over a long weekend to play a single-deck blackjack game with a 0% edge ($500 minimum). You decide to play 1,200 hands but you will quit if you bust or double your initial bankroll before reaching 1200 hands.
What size bankroll should you bring to give yourself a 1/3 chance of busting, 1/3 chance of doubling and 1/3 chance of finishing the 1200 hands without busting or doubling?
Assume a standard deviation of 1.1547, flat betting $500 one hand at a time and perfect basic strategy to realize the 0% edge
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What does the SD of 1.1547 refer to?
The blackjack game being played.Quote: ThatDonGuy[
What does the SD of 1.1547 refer to?
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Out of curiosity, what else could it refer to ?
Quote: Ace2The blackjack game being played.Quote: ThatDonGuy[
What does the SD of 1.1547 refer to?
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Out of curiosity, what else could it refer to ?
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I understand it has to do with the blackjack game - but in what way? 1.1547 of what, exactly, is within 1 SD of the mean? Is it the final win/loss result after 1200 hands?
I’m quite surprised I have to explain what standard deviation means. Look up the SD for just about any blackjack game and it’s in the 1.13 - 1.16 range
I have $50 to buy tickets. If I buy $50 worth of boxes in one pool, I have a very good chance of winning something, but am limited to one final prize. If I buy $10 worth of boxes in five pools, I have less chance in each pool, but my odds of winning multiple top prizes increase.
How do I determine the odds in each scenario?
Quote: Ace2If you play n hands of a game with an edge of x, your expectation is nx +/- n^.5 * SD. N, x and SD are defined in the problem.
I’m quite surprised I have to explain what standard deviation means. Look up the SD for just about any blackjack game and it’s in the 1.13 - 1.16 range
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I counted cards at bj for several years
but I admit that standard deviation as indicated in the question is something I did not fully understand
but I knew enough to know there was a large difference possible in the outcomes of a session or sessions even though I had a smallish advantage
the following does not answer the question posed but it helped me understand calculations behind standard deviation
it's not based on the game being equal but in a game where the player is using basic strategy and the house has about a .5% edge
it indicates that because of the rules of bj - splitting, doubling, and drawing bj the standard deviation of a game of bj is greater than that of a 50/50 coin flip
the standard deviation of a coin flip (assuming equal chance of coming heads or tails) is 0.5
the question posed is interesting and hopefully Ace or someone else will answer it and explain the calculations
"AI Overview
In blackjack, a standard deviation (SD) of approximately 1.15 units per round is the standard measure of volatility for a player using basic strategy. It quantifies how much your bankroll will fluctuate around the expected outcome (the average) due to the luck of the draw. Here is a detailed breakdown of what 1.1547 (often rounded to 1.14–1.15) means and how to use it: 1. What "1.15 Units" Means The Unit: The unit refers to your base bet. If you bet $10 per hand, your SD is $11.50 ($10 \(\times \) 1.15).Volatily Measure: Because blackjack involves doubling down and splitting pairs, the variance is higher than a simple 50/50 coin flip. The 1.15 value accounts for these extra payouts, indicating that a session of blackjack is quite volatile.Context: While the house edge might be a tiny fraction of a percent (e.g., -0.5%), the standard deviation is massive in comparison (115% of your bet).
2. How to Use 1.15 for Session Planning Standard deviation helps you determine how much money (bankroll) you need to survive, as actual results are likely to fall within 1 SD of your expected value (EV) about 68% of the time. Example (1 Hour/100 Hands):Bet: $10/hand.Expected Value (EV): Roughly -$5 (assuming -0.5% edge).SD per round: $11.50.SD for 100 hands: $11.50 \(\times \) \(\sqrt{100}\) (10) = $115.Result: In one hour, you are likely to be somewhere between winning $110 ($115 - $5) and losing $120 (-$115 - $5).
3. Key Takeaways Short-Term vs. Long-Term: In the short term (one night), standard deviation dwarfs the house edge. You can win with a negative expectation or lose with a positive one.Bankroll Requirement: The 1.15 figure helps players calculate the necessary bankroll to avoid going broke (risk of ruin).Accumulation: Standard deviation does not grow linearly. 400 hands do not have 4 times the SD of 100 hands; they have roughly 2 times (square root of the number of hands)."
.
The proper comparison would be a coin flip game in which you lose on tails and get paid 2 for 1 every time a head comes up. The standard deviation of the game is 1.Quote: lilredrooster
the standard deviation of a coin flip (assuming equal chance of coming heads or tails) is 0.5
Blackjack’s SD is a bit higher than 1 since you have <50% chance of winning a hand (before cards are dealt) and since some payouts are higher than 2 for 1.

