SSCI 2910U Lecture Notes - Lecture 4: Simple Random Sample, Statistical Inference, Statistic
12 Feb 2018
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Document Summary
25 multiple choice: scenarios, calculations within the multiple-choice question. Week 4- introduction to inferential statistics: sampling and the sampling distribution and. Basic logic and terminology of inferential statistics: population and sample, parameter and statistic, representative and epsem. Population and sample: problem: the populations we wish to study are almost always so large that we are unable to gather information from every case. Its expensive because too many resources needed: solution: we choose a sample a carefully chosen subset of the population and use information gathered from the cases in the sample to generalize to the population. Parameter and statistic: statistics = mathematical characteristics of samples, parameters = mathematical characteristics of populations, statistics are used to estimate parameters. Representative and epsem: sample must be representative of the population. Samples drawn according to the rule of epsem (equal probability of selection. Method: every case in the population has the same chance to be selected for a sample.
