Approaches to Quantitiative Analysis in the Life Sciences (Graduate)
NJIT MATH 615. Rutgers 48:120:615. 3 Credits.
Last taught by GJR: Spring 2008. Now being taught (Fall 2009).
Files for download.
Note: class guides will be posted the day after class. This is so that students will be more interactive during class itself, and so that I can make any necessary modifications based in our discussions.
General Syllabus — Class policies, grading, weekly topics, etc.
Subject Syllabus (PDF) — More detailed listing of topics week by week. This is a rough guide. Timing and order of topics are likely to change depending on how the class progresses.
Template for class project (Word) — A guide to the structure of your project. I will go through this with you.
Class 1 Guide — Probability, (lack of) intuition, data types, probability distributions, random numbers
Class 2 Guide — Probability distributions continued, quantiles, moments, goodness of fit
Class 3 Guide — Fitting models, maximum likelihood, least squares, bias
Refresher on matrix multiplication
Class 4 Guide — Three frameworks for inference: hypothesis testing, model choice, Bayesian
Class 5 Guide — ANOVA, linear models, general linear models, generalized linear models
Class 6 — R computer lab
Class 7 Guide — Prediction, cross-validation, overfitting, multiple tests (this contains some material we did not get to in class)
Class 8 Guide — Experimental design, types of errors, power
Class 9 Guide — Autocorrelation
Class 10 Guide — Non-parametric statistics
