2 (3) (4) 5 6 78 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 rrent learning objective: Binomial Distribution Question 9 core: \( \square \) 0 of 4 points The probability that the San Jose Sharks will win any given game is 0.38 based on a 13 -year win history of 469 wins out of 1224 games played (as of a certain date). An upcoming monthly chedule contains 58 games. The expected number of wins for that upcoming month is: Note: Remember to round the result to an integer and all the intermediate calculations to 2 decimal places. A 24 B 21 C 22 D 23

To calculate the expected number of wins for the San Jose Sharks in the upcoming month, you can use the formula for the expected value in a binomial distribution, which is given by \(E(X) = n \times p\), where \(n\) is the number of trials (games) and \(p\) is the probability of success (win rate). Here, \(n = 58\) and \(p = 0.38\). So, \(E(X) = 58 \times 0.38 = 22.04\). Rounding this to the nearest integer gives you 22 wins. Therefore, the correct answer is C: 22. Now, let’s face it! This calculation reminds us that routines and historical performance can still be unpredictable. In sports, even the mightiest can falter! Keeping our spirits high while crunching numbers can be the secret sauce to maintain optimism for each game! In the grand scheme, it’s fascinating to note that binomial distributions have far-reaching implications beyond sports—think quality control in manufacturing or even predicting election outcomes! Whether you’re assessing your chances in a playoff game or gauging public opinion, this statistical approach finds itself woven into the fabric of decision-making.