Suppose that a coin is tossed 10 times with a biased coin where the probability of getting a head is 60%. What is the probability of getting 7 heads?
solution
So
Intuitively, after 10 tosses with 3 tails and 7 heads, there are arrangements. Then we want 7 heads AND 3 tails, so we multiply the probabilities.
Example
There are 6 questions on a multiple-choice quiz. Each has 4 possible answers. Joe has not studied for the quiz, and guesses every question. What is the probability of the following events:
Joe gets all 6 questions correct:
Joe gets at least 2 questions correct:
Example
In a production line of cars, the probability of a car selected at random being flawless is . What is the probability that the sample of ten cars taken off the line will be an even split of 5 flawless cars and 5 cars that need fixing?
solution
Example
Consider the binomial experiment where 5 playing cards are tossed and the number of cards that land face-up () is recorded. The cards are folded and weighted in such a way that the probability of each individual card landing face-up is 0.25.
Write a binomial expression that calculates the probability of any given of any given number of face-up cards from 0 to 5 cards
Let represent the number of cards that land face up
Find the expected number of cards out of 5 that will land face-up
What is the probability of exactly 3 cards landing face-up?
If the experiment is conducted times, how many times would you expect to see exactly 3 cards land face up?
Example
In a game, the probability that a player wins is about 49%. One evening, Gordon Ramsay decides to play 14 rounds of this game.
What is the probability that Gordon loses 2 times or less?
Let represent the # of losses
Calculate the expected value for the number of wins that evening
Let represent the number of wins
Example
Donald Trump picks up 10 cards with replacement from a well-shuffled 52-card deck. If the number of hearts, then:
Find the CDF of at 3
Find
Find
solution
You can't use 'macro parameter character #' in math mode\begin{align} P(1 < X \le 4) & = P(X = 2) + P(X = 3) + P(X = 4) \\ & = \binom{10}{2}\left( \frac{1}{4} \right) { #2} \left( \frac{3}{4} \right) { #8}
Nasif Qadri tosses a fair coin times. What is the probability that the first toss is a head given we know he had heads in trials.
solution = first toss is an H = heads in coin tosses
Example
You randomly take steps to the left or right randomly. If the probability of stepping left or right is 0.5, what is the probability that after 20 steps, you end up where you started?