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Customers arrive to use the machine every two minutes on average. Consider a very simple model of a cash machine. A probabilistic model is one which incorporates some aspect of random variation.ĭeterministic models and probabilistic models for the same situation can give very different results. Every time you run the model, you are likely to get different results, even with the same initial conditions. The linear regression equation in a bivariate analysis could be applied as a deterministic model if, for example, lean body mass = 0.8737(body weight) - 0.6627 is used to determine the lean body mass of an elite athlete.Ī probabilistic model includes elements of randomness. Simple statistical statements, which do not mention or consider variation, could be viewed as deterministic models. Most simple mathematical models of everyday situations are deterministic, for example, the height (h) in metres of an apple dropped from a hot air balloon at 300m could be modelled by h = - 5t 2 + 300, where t is the time in seconds since the apple was dropped. Every time you run the model with the same initial conditions you will get the same results. The model can then be used to make predictions, test assumptions, and solve problems.Ī deterministic model does not include elements of randomness. When solving statistical problems it is often helpful to make models of real world situations based on observations of data, assumptions about the context, and on theoretical probability. Statistics includes the process of finding out about patterns in the real world using data.
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Deterministic and probabilistic models Teacher notes