MGCR 271 Lecture Notes - Lecture 5: Simple Random Sample, Stratified Sampling, Exploratory Data Analysis
13 Sep 2016
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These samples are very susceptible to being biased because of the tendency of getting responses from only those with strong opinions. Many respondents could be disgruntled due to a recent event or issue. Each element in the population has a known and nonzero probability of being selected for the sample. A systematic sample selects a random starting point in the population and then every kth element encountered thereafter becomes part of the sample. A stratified sample involves dividing the population into homogeneous groups that are as much alike as possible in one or more characteristics of interest. Sample data are then obtained from each stratum and combined to represent the total population. A stratified random sample of 100 male and 150 female mcgill students. A stratified random sample of a total of 100 montrealers, representing proportionately each major ethnic group. Relies on personal judgment rather than probability in order to select sample elements.
