POLS 2503 Lecture Notes - Lecture 12: Central Limit Theorem, Statistical Inference, Statistical Parameter

• School: Temple University
• Department: Political Science
• Course: POLS 2503
• Professor: Sanjeevini B.Lokhande

Document Summary

Population an entire universe of cases relevant to a study from which a sample is drawn (true population characteristics can never be known) Sample subset of units relevant to the study, derived from the population. Two types of sampling: random everyone in the population has the same chance of being included, non-random systemically chosen, more subject to selection bias, subgroups: convenience, quota, snowball. Sample statistic summary characteristic of patterns in sample data; best guess of population parameter. Population parameter characteristics of a population (inference about big t truth) Sampling error the fundamental barrier to all knowledge claims. Natural variation between the sample and the population will always be present. A sample is never identical to a population. Standard error the standard deviation of a sampling distribution which measures the average amount of error in our prediction of a population parameter; quantifies error. Sampling distribution distribution of samples from population of interest; hypothetical probability distribution predicted by central limit theorem.