BIOL-337 Lecture Notes - Lecture 1: Applied Mathematics, Standard Deviation, Terminal Velocity
9 Jan 2018
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Biology & history of stats a (cid:1005)6(cid:1004)(cid:1004)"s: best ga(cid:373)(cid:271)li(cid:374)g strategies. Ne(cid:454)t i(cid:374)sura(cid:374)(cid:272)e c then, grew from roots in biology d biological questions motivated development of basic stat tools. Biology & history of stats (darwin) a darwin: importance of variation in the world b. 1. quantitative descriptions: effect of sampling error c a(cid:374) offshoot of e(cid:448)olutio(cid:374)ar(cid:455) (cid:271)iolog(cid:455) Biology & history of stats (sir francis galton) a dar(cid:449)i(cid:374)"s cousin. Fi(cid:374)gerpri(cid:374)ts, prea(cid:272)her"s a(cid:374)d pra(cid:455)er, (cid:862)attra(cid:272)ti(cid:448)e(cid:374)ess(cid:863) c twin interests: evolution & data analysis d regression e esta(cid:271)lished (cid:862)the la(cid:271)(cid:863) Correlation coefficient, chi squared test c standard deviation. Anova, likelihood, p-value c randomized experiments d multiple regression e etc. Is it to decide when an effect is statistically significant? (ex: p-value) We te(cid:374)d to : jump to conclusions, be overconfident, see patterns in random data pattern, do(cid:374)"t li(cid:374)k (cid:448)aria(cid:271)ilit(cid:455) to sa(cid:373)ple size, fooled by multiple comparisons, ignore alternate explanations: biases, crave crisp conclusions: probabilities!
