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What is a model in which each outcome has an equal probability of occurring?
Wiki User
∙ 10y ago
A uniform distribution.
A uniform distribution.
A uniform distribution.
A uniform distribution.
Wiki User
∙ 10y ago
Wiki User
∙ 10y agoA uniform distribution.
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How do you compute the probability of an event?
There are two main ways: One is to calculate the theoretical probability. You will need to develop a model for the experiment and then use the laws of science and mathematics to determine the probability of the event (subject to the model's assumptions). A major alternative is the empirical or experimental method. This requires performing the trial many times. The probability of the event is estimated by the proportion of the total number of trials which result in the outcome of interest occurring.
When could you use theoretical probability?
When there is a good theoretical model for the experiment and the model allows you to identify all the factors affecting the outcome and determine their impact on the outcome. Even if you cannot identify all the factors, you can still use theoretical probability but the predictions from your model will be less reliable. Econometrics is a good example of using theoretical probability based on an incomplete understanding of the model.
How do you find the theoretical probability of an outcome?
The first step is to find a model that adequately represents the situation. You then apply reasoning based on the laws of science, along with some assumption regarding the model, to find out how likely a given outcome is. That value is its theoretical probability.
What is the meaning of the word likelihood?
In statistics, a likelihood function (often simply likelihood) is a function of a statistical model. The likelihood of a set parameter values, given outcomes x, is equal to the probability of those observed outcome.
What is the Difference between fuzzy logic and probability?
The difference between probability and fuzzy logic is clear when we consider the underlying concept that each attempts to model. Probability is concerned with the undecidability in the outcome of clearly defined and randomly occurring events, while fuzzy logic is concerned with the ambiguity or undecidability inherent in the description of the event itself. Fuzziness is often expressed as ambiguity rather than imprecision or uncertainty and remains a characteristic of perception as well as concept.
How do you compute the probability of an event?
There are two main ways: One is to calculate the theoretical probability. You will need to develop a model for the experiment and then use the laws of science and mathematics to determine the probability of the event (subject to the model's assumptions). A major alternative is the empirical or experimental method. This requires performing the trial many times. The probability of the event is estimated by the proportion of the total number of trials which result in the outcome of interest occurring.
When could you use theoretical probability?
When there is a good theoretical model for the experiment and the model allows you to identify all the factors affecting the outcome and determine their impact on the outcome. Even if you cannot identify all the factors, you can still use theoretical probability but the predictions from your model will be less reliable. Econometrics is a good example of using theoretical probability based on an incomplete understanding of the model.
How do you find the theoretical probability of an outcome?
The first step is to find a model that adequately represents the situation. You then apply reasoning based on the laws of science, along with some assumption regarding the model, to find out how likely a given outcome is. That value is its theoretical probability.
How do you determine the number of times an event will occur?
You cannot determine the number of times an event will occur - unless its probability is 0 or 1. In other cases, you can estimate the expected number of times it will occur. If the outcome of each trial is independent, then the expected number is the probability of the event occurring in one trial multiplied by the number of trials. If the outcome of each trial is not independent then you need to develop a model that takes account of the dependencies.
What is the meaning of the word likelihood?
In statistics, a likelihood function (often simply likelihood) is a function of a statistical model. The likelihood of a set parameter values, given outcomes x, is equal to the probability of those observed outcome.
What is the Difference between fuzzy logic and probability?
The difference between probability and fuzzy logic is clear when we consider the underlying concept that each attempts to model. Probability is concerned with the undecidability in the outcome of clearly defined and randomly occurring events, while fuzzy logic is concerned with the ambiguity or undecidability inherent in the description of the event itself. Fuzziness is often expressed as ambiguity rather than imprecision or uncertainty and remains a characteristic of perception as well as concept.
What is Monte Carlo Simulation?
Monte Carlo (MC) simulation is a quantitative risk analysis technique in which uncertain inputs in a model (for example an Excel spreadsheet) are represented by probability distributions (instead of by one value such as the most likely value). By letting your computer recalculate your model over and over again (for example 10,000 times) and each time using different randomly selected sets of values from the (input) probability distributions, the computer is using all valid combinations of possible input to simulate all possible outcomes. The results of a MC simulation are distributions of possible outcomes (rather than the one predicted outcome you get from a deterministic model); that is, the range of possible outcomes that could occur and the likelihood of any outcome occurring. This is like running hundreds or thousands of "What-if" analyses on your model, all in one go, but with the added advantage that the 'what-if' scenarios are generated with a frequency proportional to the probability we think they have of occurring.
Where is probability use?
Where the outcome of an event is affected by chance or random elements, or where there are too many contributory factors and it is not possible to accommodate all of them in a model so that the outcome appears to be affected by chance. The weather may be considered as an example of the latter.
How do you test theoretical probability?
The theoretical probability provides a model for predicting the outcome of trials. You then carry out a number of trials. Compare the outcome of your trials with the results predicted by the theoretical model. The comparison will usually involve "hypothesis testing", a branch of statistics. This is a method to test how likely the actual outcomes are if the theoretical probabilities were true. The exact nature of the test will depend on the theoretical basis and so the answer cannot be simplified.
How do you compute the p-value?
The first step in calculating a p-value is to make a hypothesis of the statistical model for your study. You then assume that the hypothesis is true and calculate the probability of observing an outcome at least as extreme as the one that you did observe. This probability is the p-value.
How would you calculate the probability of an event occurring?
There are two main methods: theoretical and empirical. The first of these is used when there is a relatively simple model for the possible outcomes of a trial. For example, if you roll a fair die, laws of physics suggest that each of the six faces is equally likely to end up on the top face. The probability for each of the six numbers is, therefore, 1/6. The second method is used when there is no satisfactory model based purely on theory: if you have a loaded die, for example. It may, just about, be possibly to analyse the physical properties of the mass distribution within the coin and develop an appropriate model for the outcome of a throw. However, it is simpler to use the second method. Given the chance, roll the die again and again (and again and again and ... ) and record the outcomes. The probability of any particular outcome is the proportion of the trials that result in that particular event. Thus, if a loaded die comes up 6 fifty times out of 200 throws, then the probability of throwing a 6 is 50/200 = 0.25.
What is Theoretical Probabilty?
In theoretical probability, the probability is determined by an assumed model (for example, the normal distribution). (compare with empirical probability)
