EEMB 146 Lecture Notes - Lecture 1: Biostatistics, Statistical Parameter, Sampling Error
4 Apr 2018
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Document Summary
The application of statistical analysis to biological data. Usually we can"t measure the biological properties of the entire population so we have to infer these properties from a sample. There is almost always variability in the biological properties. Population: all of the individuals or units of interest. Sample: a subset of units taken from the population. Estimation: the process of inferring an unknown quantity of a population using sample data. Parameters: quantities describing populations (e. g. averages, proportions, measures of variation) Estimate: the related quantities calculated from a sample (the mean number, etc. ) Sampling error is the chance difference between an estimate and the population parameter being estimated. Bias is a systematic discrepancy between estimate and the true population parameter. An accurate (unbiased) estimate is center on the correct value. In a random sample, each member of a population has an equal and independent chance of being selected.
