In the article, “What are the chances Paul the octopus is right?” by Sarah Shenker and “Octopus Beats ‘Vampire Squid’ as Goldman Falls Short in World Cup” by Neelabh Chaturvedi, we are exposed about Paul, the octopus, forecasting accurate results for six of Germany’s World cup games. Learning about probabilities in class, we are trying how we can interpret rules and terms about probability to Paul the octopus selecting the winning team.
In the BBC article, Sarah Shenker states, “[Paul] had a 1/64 chance of predicting six correct outcomes.” The author reaches the probability of 1/64 by multiplying the chances of predicting for each game. For example, in the article, Paul had a 1/2 chance of predicting the first game correctly, 1/4 chance of predicting the first ...view middle of the document...
So, in the tank, I would drop two clear boxes decorated with different team flags on the front containing food inside each one. However, in my “experiment,” I would add another clear box decorated with both opposing flags to symbolize “draw” as one of the results. My new predicting octopus “experiment” has the different chances for predicting each game. Because Paul the octopus only has 33% or 1/3 chance of predicting the winning team between the three options, we would just multiple another 33% or 1/3 to the previous game.
For example, my new octopus would have 1/3 chance of predicting the first game, 1/9 chance of predicting the first two games, 1/27 chance of predicting the first three games, and more. In my version of the “experiment,” I would say the odds for my octopus successfully predicting the outcome of 6 games in a row would be 1/729.
Analyzing Goldman Sach’s econimc prediction to random guessing (randomly guessing one of three outcomes),
Comparing Goldman Sach’s economic team predicting 37.5 success rate for only 8 games and prediction of 37.5% success rate from 48 games, I would feel a stronger evidence from the 37.5% success rate from the 48 games because of the Law of Large Numbers. Based on the Law of Large Numbers, we can assume the assumption from the 48 games would be closer to the theoretical probability value of success rates than only 8 games. Also, I believe the increase in the sample size would correlate to the decrease in margin of error.
If Paul the Octopus lived long enough to guess the outcomes of 48 games, I would predict the success rate would have been very very low.
Besides Paul the Octopus, I thought of other examples of the prediction system like, weather forecast systems,