Experimental Design

Introduction - designing, in the sense of scheming; a framework for investigating biological patterns and processes - it's the thought that counts; populations, frequency distributions and samples - statistics, damn statistics and lies; statistical tests of null hypotheses - how often do I get the wrong answer?; statistical tests on samples - becoming testy; simple experiments comparing the means of two populations - it's so easy a student can do it; hypotheses about entire frequency distributions - getting fit; introduction to relationships between two variables - the shortest distance between two points might be a straight line; analysis of variance - many samples don't make light work; more analysis of variance (because you can't have enough of a good thing); nested analyses of variance; factorial experiments; mixtures of fixed and random factors (muddled models); construction of any analysis from general principles; some common and some particular experimental designs; analysis of co-variance or measuring progress on parallel tracks; experiments involving circular data - getting an angle on things; conclusions - where to from here?