Final answer:
The difference between Mr. Novick's real-world results and the probability model's predictions is due to the small number of games played. In the short term, it's possible to have a winning streak that deviates from long-term expectations. The small sample size explains the variance, not Mr. Novick's awareness of the odds.
Step-by-step explanation:
The real-world results of Mr. Novick winning 100% of the two times he has played his favorite casino game differ from the probability model's prediction because of real-world variance and the small sample size. The probability model predicts a 45% chance of winning, but with only two games played, it's entirely possible to deviate from these expectations. The law of large numbers indicates that more trials are needed for the observed probability to align with the expected probability.
Statistics often deal with probabilities and expected outcomes over a long period or many trials, not the outcome of a few instances. Thus, Mr. Novick's short-term streak does not conflict with the long-term probability predictions. It is the small number of games played that explains why his real-world results may differ from what the probability model predicts (option B). Knowledge of or belief in the probability does not influence the actual outcomes of the games (eliminating option A).
The fact that Mr. Novick has won 100% of the two times he has played his favorite casino game is due to random chance. In probability, it is possible for unlikely events to occur in a small number of trials. The probability model predicts that Mr. Novick will win 45% of the time and lose 55% of the time, but this is based on long-term averages and is not guaranteed to happen in every individual trial. Therefore, the real-world results of Mr. Novick winning 100% of the two times he played the game could simply be the result of luck.