Statistical Sciences 1023A/B Lecture Notes - Systematic Sampling, Cluster Sampling, Simple Random Sample
19 Sep 2013
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Document Summary
After data is collected, a sample is necessary. The process of selecting a sub-collection of individuals/units from a population for a study. Population: set of all things we are interested in i. e. students in stat. Sample: collection of units that we actually measure. Sampling frame: set of all units from which we obtain our sample. Ideally, sampling frame = population i. e. conducting a study on canadian population. Sampling frame composed of those with phones. Ways to obtain this: simple random sample (srs): each possible sample of a required size has an equal chance of being selected randomly selecting units from the sample. Best and easiest method of obtaining a representative sample. Other sampling strategies: stratified random sampling: population is split into 2+ strata, then a random sample is drawn from each strata, cluster sampling: pop. Divided into regions, then random sample of regions are censured. Units outside the population are brought in. Self-selected samples and convenience samples (e. g. sampling friends).
