To expect a sequence of events generated by a random process will represent essential characteristics of that process even when the sequence is short.

To expect a sequence of events generated by a random process will represent essential characteristics of that process even when the sequence is short.

• A. Gambler's fallacy
• B. Law of small numbers
• C. Misconception of chance
• D. Representativeness bias

Answer: (C)

A short sequence from a random process can easily look like it reflects the whole process, even though it doesn’t. This mistake—expecting the tiny sample to reveal the underlying characteristics with certainty—is a misconception of chance. Random variation in small samples can produce runs or patterns that seem meaningful, but they don’t guarantee the same proportions will hold in the long run. Over many trials, the observed frequencies tend to approach the true probabilities, but a brief sequence often isn’t representative.

A short sequence from a random process can easily look like it reflects the whole process, even though it doesn’t. This mistake—expecting the tiny sample to reveal the underlying characteristics with certainty—is a misconception of chance. Random variation in small samples can produce runs or patterns that seem meaningful, but they don’t guarantee the same proportions will hold in the long run. Over many trials, the observed frequencies tend to approach the true probabilities, but a brief sequence often isn’t representative.