EAS100 Lecture Notes - Lecture 15: Statistical Parameter, Cluster Sampling, Confounding

• School: University of Alberta
• Department: Earth and Atmospheric Sciences
• Course: EAS100
• Professor: Jeffrey Kavanaugh

Document Summary

Census is a special sample that includes everyone and. There are problems with taking a census: cost, undercount, time, complexity. A parameter that is part of a model for a population is called a population parameter (often unknown) A summary that is found from data in a sample are called sample statistics (are known once the data are observed) Two types of conclusions (inferences: population inference. Results from the sample can be generalized to an entire population (as estimates) Ch 9 11 gathering data: causal (cause-and-effect) inference. The difference in the responses is caused by the difference in treatments when comparing the results from two treatment groups. Randomizing makes sure that on the average the sample looks like the rest of the population: non-random sampling leads to biased results (results that tend to over- or under- emphasize some characteristics of the population)