TESTING AND COURSE AIMS
This course has two assignments and one presentation that together serve as a test:
Assignments:
a. Students are able to implement and use basic methods for statistical inference, as well as more advanced ones such as the bootstrap and permutation test (Applying)
b. Students will have developed fundamental and computationally efficient R programming skills (Applying)
c. Students are able to conduct and report on simulation studies, comparing the performance of statistical methods in specific settings (Applying, Communication)
d. Students are familiar with some widely used numerical methods (Knowledge and Understanding)
e. Students are able to translate new statistical methods from the literature into a usable R program (Judgment)
Students develop fundamental knowledge and understanding in principles of computational statistical inference.(Knowledge and Understanding)
f. Students are capable of finding solutions to problems from the R help system, discussion fora and Google (Learning skills)
Presentation:
a. Students are able to present on Assignment 2, showing the ability to present statistical problems to specialist and non-specialist audiences clearly and unambiguously in English (Communication)
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