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Probability, Statistics and Information - MATH2859 |
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Description Sample spaces, probability, random variables and probability distributions. Examples of discrete and continuous distributions. Central Limit Theorem. Statistical inference, confidence intervals and hypothesis testing. Bivariate normal distribution, optimal mean square estimation, introduction to the multivariate normal distribution. Linear regression and least squares estimation. Inference in the linear model. On-line and off-line estimation. Statistical quality control. Models, applications and statistical algorithms relevant to the fields of computer, electrical, software and telecommunications engineering.
Note: Available only to students for whom it is specifically required as part of their program. |