Answer: Sample mean converges almost surely to population mean.
- A Sample mean converges in probability to population mean
- B Sample mean converges almost surely to population mean
- C Sample variance is generally assumed correct without further checking
- D This applies mainly to normal distributions specifically
Correct answer: B. Sample mean converges almost surely to population mean
Explanation: Strong LLN: sample mean converges almost surely (with probability 1) to expected value. Stronger than weak LLN (convergence in probability).
Venn diagram of the universal set U with events A and B, showing the intersection (A and B), the parts unique to each event, and the complement region outside both.
Concept context
Chance, events, conditional probability, and Bayes theorem