Qm
Foundational

Why HHH Takes Longer to Appear Than HHT

Two 3-flip patterns with identical single-shot probability take very different average numbers of flips to first appear, because one can reuse partial progress toward itself and the other can't.

Prerequisites: Conditional Probability

The problem. Flip a fair coin repeatedly. On average, how many flips until you first see HHH? How many until you first see HHT? Both are specific 3-flip sequences, each with probability 18\frac{1}{8} of occurring in any given window of 3 flips, so it's tempting to guess the waiting times are equal. They aren't: HHT appears after 8 flips on average, while HHH takes 14. The gap comes entirely from what happens when a near-miss occurs.

The key idea: what a failed attempt leaves behind

Suppose you're chasing HHH and you've just flipped H, H, and then the coin comes up T. You needed HHH but got HHT, total failure, and you have to start over from scratch, because a T wipes out any H-streak. Now suppose you're chasing HHT and you've flipped H, H, then the third flip comes up H again (not T). You haven't completed HHT, but you haven't lost anything either, you still have "HH" as your current progress, exactly where you'd want to be if you're two flips into building toward HHT. A failed attempt at HHT still leaves useful partial progress behind; a failed attempt at HHH (specifically, hitting a T after any number of H's) destroys all progress instantly.

Worked example: setting up the states for HHT

Model progress toward HHT as a Markov chain with states: S0S_0 (no useful progress), SHS_H (just saw an H), SHHS_{HH} (just saw HH), and "done" (saw HHT). From S0S_0: flip H moves to SHS_H (prob 12\frac12), flip T stays at S0S_0 (prob 12\frac12). From SHS_H: flip H moves to SHHS_{HH}, flip T moves back to S0S_0. From SHHS_{HH}: flip H stays at SHHS_{HH} (because "HH" is still valid progress toward HHT after another H), flip T completes to "done." Let E0,EH,EHHE_0, E_H, E_{HH} be expected additional flips from each state:

EHH=1+12EHH+12(0)    EHH=2.E_{HH} = 1 + \tfrac12 E_{HH} + \tfrac12(0) \;\Rightarrow\; E_{HH} = 2. EH=1+12EHH+12E0,E0=1+12EH+12E0.E_H = 1 + \tfrac12 E_{HH} + \tfrac12 E_0, \qquad E_0 = 1 + \tfrac12 E_H + \tfrac12 E_0.

Solving: from the E0E_0 equation, 12E0=1+12EH\tfrac12 E_0 = 1 + \tfrac12 E_H, so E0=2+EHE_0 = 2 + E_H. Substituting into EH=1+12(2)+12E0=2+12(2+EH)=3+12EHE_H = 1 + \tfrac12(2) + \tfrac12 E_0 = 2 + \tfrac12(2+E_H) = 3 + \tfrac12 E_H, giving EH=6E_H = 6, and E0=8E_0 = 8. Starting from scratch, HHT takes 8 flips on average.

Why HHH is worse: self-overlap costs you the progress

Redo the chain for HHH: from SHHS_{HH} (just saw HH), a flip of H completes HHH, but a flip of T sends you all the way back to S0S_0, unlike HHT's chain, where the failing flip only cost you the "T" attempt while H kept you at SHHS_{HH}. Solving the analogous equations gives E0=14E_0 = 14 for HHH, a full 6 flips worse than HHT, purely because every near-miss on HHH (a T after any H's) wipes the slate clean, while HHT's near-misses (extra H's) do not.

Path explorer
13055time →
end (bold path) 100.38spread of ends 58.966 independent paths, same settings

Think of each sample path above as a run of coin flips: the "waiting time" question asks how long, on average, before a specific short pattern first appears somewhere along the path, a natural first-passage question the explorer's paths make visually intuitive.

Two equally probable patterns can have very different expected waiting times. The determining factor is self-overlap: patterns whose prefixes can reappear as suffixes (like HH inside HHH) let a near-miss still count as partial progress, or in HHH's specific case, let a single wrong flip erase all progress, model the chase as a Markov chain over "current progress" states to get the exact number.

Don't assume equal single-window probability means equal waiting time. 18\frac18 probability per 3-flip window is about the chance in one shot; expected waiting time is about how much progress survives a near-miss, which depends on the pattern's internal structure, not on its raw probability.

Discussion

Sign in to join the discussion · reading is open to everyone

💡 Discussion rules

  1. Ask and answer about this concept. Off-topic gets removed.
  2. No homework dumps. Show what you tried first.
  3. Corrections are welcome. Cite a source when you claim an error.

Loading discussion…

Related concepts

Practice in interviews

Further reading

  • Grinstead & Snell, Introduction to Probability, ch. 11
ShareTwitterLinkedIn