BIOL 141 Lecture Notes - Lecture 3: Standard Error, Standard Deviation, Observational Error
Document Summary
Systemic error: error in specific direction; shifts the mean in one direction. Can be reduced by normalizing data to controls or randomizing data so that all groups are equally effected: example: slow reflexes when turning off uv light (leads to more exposure than intended) Random error: error without directional bias; just leads to greater variation in data. Can be reduced by using replicates: example: we might not count the correct number of colonies; may be overestimation or underestimation. Standardizing data: co(cid:374)(cid:448)e(cid:396)ti(cid:374)g data f(cid:396)o(cid:373) (cid:858)(cid:396)a(cid:449)(cid:859) (cid:374)u(cid:373)(cid:271)e(cid:396)s (cid:894)e. g. (cid:272)ou(cid:374)ts(cid:895) to a pe(cid:396)(cid:272)e(cid:374)tage o(cid:396) proportion to make it more meaningful. Scientists often perform replicate experiments in order to gain confidence in their findings and reduce effects of random error. However, identifying trends in large numbers of datapoints or graphing large numbers of datapoints can be difficult. Thus scientists often combine replicate data in order to allow for simple comparisons and visualizations for trends.
