1. Describe how you can find the theoretical probability of an outcome. Why is it called a theoretically probability?
Theoretical probability is used to find the likeliness of an outcome of the probability of an outcome, just like experimental probability. However, there are some critical differences between these two types of probability methods. While the experimental probability of an outcome is found by conducting an actual experiment, theoretical probability is found by observing a situation and using calculations to come up with the probability of an outcome. Theoretical probability does not need you to perform an experiment to find the likelihood of a desired outcome. For example, let's say that there are two coins, and you wanted to see the likelihood of the outcome to be a match (HH or TT). Instead of actually performing an experiment with a good amount of trials, you would analyze the situation an then use calculations to form a theory. Here is how you would execute the theoretical probability for the problem stated above. First, I know that the probability of getting a heads or a tails on one coin is P(H or T)=1/2. This would be the same for the other coin, as there are still two sides. Then, you would multiply the 1/2 twice as there are only two coins: 1/2 * 1/2= 1/4. So, there is a 1/4 chance that there will be a match. This is using theoretical probability. Overall, it's called theoretical probability because your conclusions and your later predictions are based off of your theory of a situation. And remember, something that is theoretical is only an idea, not an actual or physical thing. Something that is theoretical is only an idea.
2. a. Suppose two people do an experiment to estimate the probability of an outcome. Will they get the same probabilities? Explain.
This is a bit of a tricky question. This depends on the actual experiment performed by the two people as well as the number of trials that were executed in the experiment itself. It is possible that both people get the same results, or get results close to each other's. For example, let's say that a girl name Anya and a girl named Riya were both going to toss a coin 100 times. The theoretical probability probability of it landing on either heads or tails: P(H or T)=1/2. There is a 50% chance that the coin could land on either side when tossing the coin. So, when flipping the coin, you would believe that the results would support exactly that. However, the experimental probability may show otherwise. It's not certain that out of 100 flips, there would be 50 heads and 50 tails. Although that is not likely, it is likely to get the experimental probability with a 50-50 chance of it landing on either heads or tails. It is also likely that the coin will land close to 50 heads and 50 tails. Going back to the original question, it is not 100% certain that the two students who perform the experiment will get the same results. Their conclusions and outcomes are all dependent on how the experiment itself is set up (how many trials are performed) and the way that the information is presented.
b. Two people analyze a situation to find the theoretical probability of an outcome. Will they get the same probabilities? Explain.
These people should get the same theoretical probability. Theoretical probability is only based on what the probability should be in THEORY. There is no factor that could influence one's result to be different from the other's. However, as we know what happens in real life, people make errors in their calculations or just don't understand the concepts. Apart from those minor factors, there is no reason for the results of the theoretical probability to differ. So for example, if they are examining a spinner with four colors (red, green, yellow, and blue), all colors of equal size, then both of the people's their theoretical probability should end up the same. The theoretical probability of the spinner landing on yellow is 1/4. This theoretical probability will always stay the same, unlike experimental probability which can change.
c. One person uses an experiment to estimate the probability of an outcome. Another person analyzes the situation to find the theoretical probability of the outcome. Will they get the same probabilities? Explain.
The experimental probability of an outcome is likely to be close to the theoretical probability of the outcome. If we use the same example from question 2a, the theoretical probability that Anya or Riya would land on heads would be 1/2 or 50/100. Yet , neither people actually got exactly 50/100. Each of their experimental probabilities were different. The results showed that when it came to Anya's set of data, there was a 53% chance that her coin would land on heads after being tossed. 53% is quite close to 50% but not exact. But, Riya had a 46% of her coin landing on heads after tossing it. 46% is not close to 50%, this shows that it is also likely that they will not get the same probabilities when finding the experimental and theoretical probabilities. But remember, it is likely that they will get probabilities close to one another. Sometimes the experimental probability can be affect by how you execute it and how may trials, this will change how accurate and closer to the theoretical probability the data is. Overall, it is quite unlikely that the people will get the exact same outcome when finding the theoretical and experimental probabilities.
3. What does it mean for a game to be fair?
For a game to be fair, there has to be an equal chance of winning and losing for each player. This doesn't mean that each player had to have a 50% chance of winning to be fair. it just means that each player has an EQUAL chance of winning. A game is also fair if there is a "fair" way of winning. To calculate this, you need to know the number of player that are playing. The, you would divide the full 200% evenly among the players. So, if there are 5 players, and the game is "fair", this would mean that each plater had a 20% chance of winning, which is fair. You can only do this when you know the the game is certainly "fair".
4. What is a sample space, and how can it be repeated?
A sample space is a list of all the possible outcomes from an experiment or any other given situation. This means that you have a list of all the possibilities written down. Generating a sample space can be extremely helpful when finding the likelihood of an outcome as you can see, right in front of you, all the possibilities. A sample space will help you get a deeper understanding of what the game could look like and show you if the game is "fair" or not. Generating a sample space is actually quite easy.One strategy when generating a sample space is drawing a tree diagram. The picture on the side an example of a tree diagram. This diagram shows the possible outcomes when tossing three coins. Another way to show a sample space is creating a matrix.
Theoretical probability is used to find the likeliness of an outcome of the probability of an outcome, just like experimental probability. However, there are some critical differences between these two types of probability methods. While the experimental probability of an outcome is found by conducting an actual experiment, theoretical probability is found by observing a situation and using calculations to come up with the probability of an outcome. Theoretical probability does not need you to perform an experiment to find the likelihood of a desired outcome. For example, let's say that there are two coins, and you wanted to see the likelihood of the outcome to be a match (HH or TT). Instead of actually performing an experiment with a good amount of trials, you would analyze the situation an then use calculations to form a theory. Here is how you would execute the theoretical probability for the problem stated above. First, I know that the probability of getting a heads or a tails on one coin is P(H or T)=1/2. This would be the same for the other coin, as there are still two sides. Then, you would multiply the 1/2 twice as there are only two coins: 1/2 * 1/2= 1/4. So, there is a 1/4 chance that there will be a match. This is using theoretical probability. Overall, it's called theoretical probability because your conclusions and your later predictions are based off of your theory of a situation. And remember, something that is theoretical is only an idea, not an actual or physical thing. Something that is theoretical is only an idea.2. a. Suppose two people do an experiment to estimate the probability of an outcome. Will they get the same probabilities? Explain.
This is a bit of a tricky question. This depends on the actual experiment performed by the two people as well as the number of trials that were executed in the experiment itself. It is possible that both people get the same results, or get results close to each other's. For example, let's say that a girl name Anya and a girl named Riya were both going to toss a coin 100 times. The theoretical probability probability of it landing on either heads or tails: P(H or T)=1/2. There is a 50% chance that the coin could land on either side when tossing the coin. So, when flipping the coin, you would believe that the results would support exactly that. However, the experimental probability may show otherwise. It's not certain that out of 100 flips, there would be 50 heads and 50 tails. Although that is not likely, it is likely to get the experimental probability with a 50-50 chance of it landing on either heads or tails. It is also likely that the coin will land close to 50 heads and 50 tails. Going back to the original question, it is not 100% certain that the two students who perform the experiment will get the same results. Their conclusions and outcomes are all dependent on how the experiment itself is set up (how many trials are performed) and the way that the information is presented.
b. Two people analyze a situation to find the theoretical probability of an outcome. Will they get the same probabilities? Explain.
These people should get the same theoretical probability. Theoretical probability is only based on what the probability should be in THEORY. There is no factor that could influence one's result to be different from the other's. However, as we know what happens in real life, people make errors in their calculations or just don't understand the concepts. Apart from those minor factors, there is no reason for the results of the theoretical probability to differ. So for example, if they are examining a spinner with four colors (red, green, yellow, and blue), all colors of equal size, then both of the people's their theoretical probability should end up the same. The theoretical probability of the spinner landing on yellow is 1/4. This theoretical probability will always stay the same, unlike experimental probability which can change.c. One person uses an experiment to estimate the probability of an outcome. Another person analyzes the situation to find the theoretical probability of the outcome. Will they get the same probabilities? Explain.
The experimental probability of an outcome is likely to be close to the theoretical probability of the outcome. If we use the same example from question 2a, the theoretical probability that Anya or Riya would land on heads would be 1/2 or 50/100. Yet , neither people actually got exactly 50/100. Each of their experimental probabilities were different. The results showed that when it came to Anya's set of data, there was a 53% chance that her coin would land on heads after being tossed. 53% is quite close to 50% but not exact. But, Riya had a 46% of her coin landing on heads after tossing it. 46% is not close to 50%, this shows that it is also likely that they will not get the same probabilities when finding the experimental and theoretical probabilities. But remember, it is likely that they will get probabilities close to one another. Sometimes the experimental probability can be affect by how you execute it and how may trials, this will change how accurate and closer to the theoretical probability the data is. Overall, it is quite unlikely that the people will get the exact same outcome when finding the theoretical and experimental probabilities.
3. What does it mean for a game to be fair?
For a game to be fair, there has to be an equal chance of winning and losing for each player. This doesn't mean that each player had to have a 50% chance of winning to be fair. it just means that each player has an EQUAL chance of winning. A game is also fair if there is a "fair" way of winning. To calculate this, you need to know the number of player that are playing. The, you would divide the full 200% evenly among the players. So, if there are 5 players, and the game is "fair", this would mean that each plater had a 20% chance of winning, which is fair. You can only do this when you know the the game is certainly "fair".
4. What is a sample space, and how can it be repeated?
A sample space is a list of all the possible outcomes from an experiment or any other given situation. This means that you have a list of all the possibilities written down. Generating a sample space can be extremely helpful when finding the likelihood of an outcome as you can see, right in front of you, all the possibilities. A sample space will help you get a deeper understanding of what the game could look like and show you if the game is "fair" or not. Generating a sample space is actually quite easy.One strategy when generating a sample space is drawing a tree diagram. The picture on the side an example of a tree diagram. This diagram shows the possible outcomes when tossing three coins. Another way to show a sample space is creating a matrix.











