Understanding statistics in technometrix plant simulation

#Understanding statistics in technometrix plant simulation how to#
#Understanding statistics in technometrix plant simulation professional#
#Understanding statistics in technometrix plant simulation simulator#

Medical students, for example, learn on plastic patients that are programed to exhibit all manner of symptoms in rapid succession.

#Understanding statistics in technometrix plant simulation professional#

Given the success in industry and government, it is not surprising that simulation is found in professional schools in universities.

#Understanding statistics in technometrix plant simulation simulator#

Airlines require pilots to log simulator hours, electrical engineers conduct simulations on a daily basis to check load requirements, the Pentagon simulates potential conflicts, and so on.Simulations are among the most often used pedagogies in industry and government. This is one of the most significant outcomes of simulation in social science disciplines such as sociology and political science. seeing social processes and social interactions in action.A well done simulation includes a strong reflection summary that requires students to think about how and why they behaved as they did during the simulation. understanding and refining their own thought processes.A well done simulation is constructed to include an extension to a new problem or new set of parameters that requires students to extend what they have learned in an earlier context. transferring knowledge to new problems and situations.Students are active participants in selecting parameter values, anticipating outcomes, and formulating new questions to ask. Instructional simulations by their very nature cannot be passive learning. actively engaging in student-student or instructor-student conversations needed to conduct a simulation.Learn to reflect on and extend knowledge by Simulations help students understand that scientific knowledge rests on the foundation of testable hypotheses.

#Understanding statistics in technometrix plant simulation how to#

how to use a model to predict outcomes.

Given the utility of data simulation, it is not surprising that SERC has an existing module on teaching with data simulation. The ability to match simulation results with an analytically derived conclusion is especially valuable in beginning classes, where students often struggle with sampling theory. Instructional simulations have proven their worth many times over in the statistics based fields. Simulations help students understand probability and sampling theory.

data issues, probability and sampling theory.

Students develop a feel for what variables are important and the significance of magnitude changes in parameters. Simulation allows students to change parameter values and see what happens.

the relationships among variables in a model or models.

Using instructional simulations gives students concrete formats of what it means to think like a scientist and do scientific work. Experiments and simulations are the way scientists do their work. Deep learning means that students: Learn scientific methods including

A good summary of how deep learning contrasts with surface learning is given at the Engineering Subject Centre: Deep and Surface Approaches to Learning. Instructional simulations have the potential to engage students in 'deep learning' that empowers understanding as opposed to 'surface learning' that requires only memorization.