The Coin Toss Experiment


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1 Experiments p. 1/1 The Coin Toss Experiment Perhaps the simplest probability experiment is the coin toss experiment.
2 Experiments p. 1/1 The Coin Toss Experiment Perhaps the simplest probability experiment is the coin toss experiment. We idealize slightly to assume that the experiment has only two possible outcomes, heads and tails.
3 Experiments p. 1/1 The Coin Toss Experiment Perhaps the simplest probability experiment is the coin toss experiment. We idealize slightly to assume that the experiment has only two possible outcomes, heads and tails. We also assume these are equally likely, that is, we are using a fair coin.
4 Experiments p. 1/1 The Coin Toss Experiment Perhaps the simplest probability experiment is the coin toss experiment. We idealize slightly to assume that the experiment has only two possible outcomes, heads and tails. We also assume these are equally likely, that is, we are using a fair coin. Because the probabilities of all outcomes have to add to one, the probabilities of heads and tails must both be 1/2.
5 Experiments p. 2/1 The Law of Large Numbers According to the law of large numbers, if we repeat the coin toss many times, the proportion of heads we obtain will approach 1/2 as the number of repetitions grows.
6 Experiments p. 2/1 The Law of Large Numbers According to the law of large numbers, if we repeat the coin toss many times, the proportion of heads we obtain will approach 1/2 as the number of repetitions grows. This does not mean that exactly 1/2 of the tosses will result in heads.
7 Experiments p. 2/1 The Law of Large Numbers According to the law of large numbers, if we repeat the coin toss many times, the proportion of heads we obtain will approach 1/2 as the number of repetitions grows. This does not mean that exactly 1/2 of the tosses will result in heads. What it does mean is that the proportion will be close to 1/2 when the number of tosses is large.
8 Experiments p. 2/1 The Law of Large Numbers According to the law of large numbers, if we repeat the coin toss many times, the proportion of heads we obtain will approach 1/2 as the number of repetitions grows. This does not mean that exactly 1/2 of the tosses will result in heads. What it does mean is that the proportion will be close to 1/2 when the number of tosses is large. The greater the number of tosses, the closer the proportion gets to 1/2.
9 Experiments p. 2/1 The Law of Large Numbers According to the law of large numbers, if we repeat the coin toss many times, the proportion of heads we obtain will approach 1/2 as the number of repetitions grows. This does not mean that exactly 1/2 of the tosses will result in heads. What it does mean is that the proportion will be close to 1/2 when the number of tosses is large. The greater the number of tosses, the closer the proportion gets to 1/2. As we will see, if we repeat the coin toss experiment 1,000 times, we expect the number of heads to be between 476 and 524 more than 99% of the time.
10 Experiments p. 3/1 Two Coin Tosses Now we consider the experiment of tossing a coin twice.
11 Experiments p. 3/1 Two Coin Tosses Now we consider the experiment of tossing a coin twice. The total number of heads obtained is one of the following: zero, one, or two
12 Experiments p. 3/1 Two Coin Tosses Now we consider the experiment of tossing a coin twice. The total number of heads obtained is one of the following: zero, one, or two We get an idea of the probability of these events by using the computer to simulate a large number of repetitions of this experiment, and observing the proportions of experiments that result in zero, one, or two heads.
13 Experiments p. 4/1 Two Coin Tosses We interpret the results of this simulation using the empirical approach.
14 Experiments p. 4/1 Two Coin Tosses We interpret the results of this simulation using the empirical approach. The empirical approach says that the probability of an event E is approximately P(E) number of times event E occurs number of times the experiment is repeated
15 Experiments p. 4/1 Two Coin Tosses We interpret the results of this simulation using the empirical approach. The empirical approach says that the probability of an event E is approximately P(E) number of times event E occurs number of times the experiment is repeated When we perform the simulation, we should find that we get a single heads outcome about twice as often as we get zero or two heads.
16 Two Coin Tosses We interpret the results of this simulation using the empirical approach. The empirical approach says that the probability of an event E is approximately P(E) number of times event E occurs number of times the experiment is repeated When we perform the simulation, we should find that we get a single heads outcome about twice as often as we get zero or two heads. By the empirical approach, we suspect that the probability of getting one heads is twice the probability of getting zero or two heads. Experiments p. 4/1
17 Experiments p. 5/1 Two Coin Tosses How do we explain this? One way is to use the Classical Method
18 Experiments p. 5/1 Two Coin Tosses How do we explain this? One way is to use the Classical Method The classical method says that if an experiment has n equally likely outcomes, and the number of outcomes for which we say event E has occurred is m, the the probability of the event E is: P(E) = number of ways event E can occur number of possible outcomes = m n
19 Experiments p. 6/1 Two Coin Tosses How do we explain this? One way is to use the Classical Method
20 Experiments p. 6/1 Two Coin Tosses How do we explain this? One way is to use the Classical Method Each toss has two outcomes, heads or tails, so the experiment has the following four outcomes: First Toss H H T T Second Toss H T H T
21 Experiments p. 6/1 Two Coin Tosses How do we explain this? One way is to use the Classical Method Each toss has two outcomes, heads or tails, so the experiment has the following four outcomes: First Toss H H T T Second Toss H T H T If we assume each of the four outcomes are equally likely, each must have probability 1/4.
22 Experiments p. 7/1 Two Coin Tosses If we consider the total number of heads obtained, there are three possibilities: First Toss Second Toss Number of Heads Probability H H 2 1/4 H T 1 1/4 T H 1 1/4 T T 0 1/4
23 Experiments p. 7/1 Two Coin Tosses If we consider the total number of heads obtained, there are three possibilities: First Toss Second Toss Number of Heads Probability H H 2 1/4 H T 1 1/4 T H 1 1/4 T T 0 1/4 Based on this table, we expect the event "one heads" to have probability 1/2, while the events "zero heads" and "two heads" have probability 1/4.
24 Experiments p. 8/1 Three Coin Tosses Now we consider the experiment of tossing a coin three times.
25 Experiments p. 8/1 Three Coin Tosses Now we consider the experiment of tossing a coin three times. This time the experiment has the following eight outcomes: First Toss Second Toss Third Toss Number of Heads H H H 3 H H T 2 H T H 2 H T T 1 T H H 2 T H T 1 T T H 1 T T T 0
26 Experiments p. 9/1 Three Coin Tosses If the eight outcomes are equally likely, each must have probability 1/8. Possible values for the total number of heads are 0, 1, 2 and 3.
27 Experiments p. 9/1 Three Coin Tosses If the eight outcomes are equally likely, each must have probability 1/8. Possible values for the total number of heads are 0, 1, 2 and 3. There is one outcome that produces zero heads. There are three outcomes that produces one heads.
28 Experiments p. 9/1 Three Coin Tosses If the eight outcomes are equally likely, each must have probability 1/8. Possible values for the total number of heads are 0, 1, 2 and 3. There is one outcome that produces zero heads. There are three outcomes that produces one heads. There are three outcomes that produces two heads.
29 Experiments p. 9/1 Three Coin Tosses If the eight outcomes are equally likely, each must have probability 1/8. Possible values for the total number of heads are 0, 1, 2 and 3. There is one outcome that produces zero heads. There are three outcomes that produces one heads. There are three outcomes that produces two heads. There is one outcome that produces three heads.
30 Experiments p. 9/1 Three Coin Tosses If the eight outcomes are equally likely, each must have probability 1/8. Possible values for the total number of heads are 0, 1, 2 and 3. There is one outcome that produces zero heads. There are three outcomes that produces one heads. There are three outcomes that produces two heads. There is one outcome that produces three heads.
31 Experiments p. 10/1 Three Coin Tosses The probabilities associated with zero and three heads must therefore be 1/8 because each can result from only one outcome.
32 Experiments p. 10/1 Three Coin Tosses The probabilities associated with zero and three heads must therefore be 1/8 because each can result from only one outcome. On the other hand, there are three outcomes that produce one heads, and three that produce two.
33 Experiments p. 10/1 Three Coin Tosses The probabilities associated with zero and three heads must therefore be 1/8 because each can result from only one outcome. On the other hand, there are three outcomes that produce one heads, and three that produce two. This means the probability of one heads and the probability of two heads are both 3/8.
If a fair coin is tossed 10 times, what will we see? 24.61% 20.51% 20.51% 11.72% 11.72% 4.39% 4.39% 0.98% 0.98% 0.098% 0.098%
Coin tosses If a fair coin is tossed 10 times, what will we see? 30% 25% 24.61% 20% 15% 10% Probability 20.51% 20.51% 11.72% 11.72% 5% 4.39% 4.39% 0.98% 0.98% 0.098% 0.098% 0 1 2 3 4 5 6 7 8 9 10 Number
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