This page covers statistics.
The numbers in the right hand column show the file size when zipped(expanded).
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MSM1S2 Probability & Decision Making |
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| Common distributions are introduced and their mean and variance found. Conditional probability and Bayes' Theorem is introduced and applied. | ||
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122 (143) |
MSMXS1 Foundation Of Statistical Inference |
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| Bayesian and Frequentist estimation is covered, and methods for assessing the quality of frequentist estimates are discussed. | ||
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54 (145) |
MSMXS2 Linear Statistical Models |
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| Analysis of Variance is first covered, leading towards modelling processes using the General Linear Statistical model. | Download DVI |
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54 (145) |
| Download PDF |
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433 (291) |
MSMYS3 Statistical Theory |
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| The theory underpinning most of MSMXS2 is covered, including the Cramér-Rao inequality, minimal sufficient statistics, the Rao-Blackwell Theorem, and hypothesis testing using general statistics such as the maximum likelihood ratio and the Wald statistic. | ||
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29 (47) |
| Download PDF |
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121 (240) |