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Overview,
Grading
and
Prequisites
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Overview and Grading The aim of this seven-lecture course is to introduce
students to the basics of
programming in R.
The lecture series will cover how to construct functions in R and how
to use R
to fit models to data and summarise the results of model fits
graphically as
well as using confidence intervals. Model selection will also be
discussed
briefly. Students completing this course will have much of the
background
needed to take the SAFS upper level stock assessment courses (FISH 458, 557, 558, 559). Instruction will occur during seven
2-hour lecture-lab sessions which will be held iuring the last five
weeks
of fall
quarter. All instruction will occur in MGH 044 with
each
participant at a computer (although the use of personal laptops will be
encouraged). Grading will be credit/no credit and the evaluation of
performance
will be based on completing two homework assignments (due in the 7th
and 11th weeks of the quarter). Prerequisites Students taking FISH 553 are expected to have taken FISH 552 (the SAFS introductory R course). You should be familiar with basic R commands (e.g. arithmetic operations), low levels commands such as “mean” and “var”, how to read data into R data structures with scan and read.table, and how to extract data from matrices and data.frames. FISH 553 covers likelihood theory. You should therefore review your introductory statistics, in particular the normal and Poisson probability distributions, as well as the basic laws of probability. Students with
Disabilities The |