Biology 2244A/B Lecture 2: 2 - Sampling Designs
15 Sep 2016
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Document Summary
Methods for planning experiments, obtaining data, and then organizing, summarizing, analyzing, interpreting, presenting, and drawing conclusions based on the data. Systematic favouritism in the data selection process, leading to misleading results. Procedures for selecting units from the population. All possible combinations (i. e. samples) of size n from the population are equally likely. The best method of achieving a representative sample. Difference between a sample statistic and the true population parameter, due to chance sample differences. Random sampling each unit of the population has an equal chance of being selected. Population split into 2+ strata, then a random sample is drawn from each strata. Population is divided into subgroups, then a random sample of subgroups (i. e. clusters") are censused. A starting point is randomly selected, and then units are sampled at a constant interval. If we want to draw conclusions about a population. Selection bias is a serious concern when non representative sampling is used.
