please assist with explanation

The Binomial Distribution The Binomial Distribution is a Discrete Probability Distribution that is commonly applied in statistics when a series of trials/experiments will produce a "success" or a "failure" (a binary outcome). This type of distribution may be used if the following conditions apply: The number of trials/ experiments/observations is fixed. Each observation is independent. Each observation has only one of two outcomes ("success" or "failure"). The probability of a "success" (p) is the same for each trial/experiment/observation/outcome. Apply the Binomial Distribution to a scenario. The probability that the San Jose Sharks will win any given game is 0.3694 based on a 13-year win history of 382 wins out of 1,034 games played. An upcoming monthly schedule contains 12 games. The conditions of a binomial distribution are met: The number of upcoming games is 12 (fixed trials) The outcome of one game doesn't affect other games (independent trials) Each game has a win/lose outcome (binary outcomes The probability of a "success" is the same for each trial. (p = 0.3694) Use the scenario above to determine the expected value (/) and selected probabilities below. You may wish to use the Binomial Distribution Calculator hosted by the University of lowa's Department of Mathematical Sciences. Remember: the formatting of this calculator may vary slightly from what is used in class. (link: Binomial Distribution Calculator [!) a. The expected number of wins for the upcoming schedule is? b. What is the probability that the San Jose Sharks will win exactly six games in the upcoming schedule? P(X = 6) = c. What is the probability that the San Jose Sharks win at least five games in the upcoming schedule? P(X > 5) = d. What is the probability that the San Jose Sharks will win more than seven games in the upcoming schedule? P(X > 7) =