To build models of complex socio-technical systems for improved system design and decision-making, you must have data and systems knowledge. If you want to solve problems related to the functions of random variables, Poisson processes, Markov processes etc. this [course_title] is for you to help where you can also be able to know classical statistics, hypothesis tests, regression, correlation and causation, simple data mining techniques and so on.
This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.
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|Introduction and overview||00:15:00|
|Analyzing a probability problem||00:05:00|
|Broken stick problem||00:05:00|
|Pedestrian crossing problem||00:05:00|
|Random incidence: A major source of selection bias||00:15:00|
|Random incidence and more||00:10:00|
|Markov processes and their application to queueing, part 1||00:10:00|
|Markov processes and their application to queueing, part 2||00:15:00|
|Queueing and transitions: Sampling from distributions, Gauss||00:05:00|
|Derived distributions to statistics||00:15:00|
|The Queue Inference Engine and the psychology of queueing||00:10:00|
|Beyond the physics of queueing||00:15:00|
|The Weibull distribution and parameter estimation||00:15:00|
|Descriptive statistics and statistical graphics||00:46:00|
|Analysis of variance, with discussion of Bayesian and frequentist statistics||00:15:00|
|Design of experiments, part 1||00:15:00|
|Design of experiments, part 2||00:15:00|
|Design of computer experiments||00:15:00|
|Submit Your Assignment||00:00:00|
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