BMGT 230 Lecture Notes - Lecture 2: Statistic, Response Bias, Systematic Sampling

• School: University of Maryland
• Department: Business and Management
• Course: BMGT 230
• Professor: Radu Lazar

Document Summary

Idea 1: examine a part of the whole. Population: the entire group of individuals or instances about whom we hope to learn. Sample survey: a study that asks questions of a sample drawn. Individuals in the population of interest but who are not in the sampling frame cannot be included in any sample. Bias: any systematic failure of a sampling method to represent its population. Sampling error (or sampling variability): the natural tendency of randomly drawn samples to differ, one from another. Idea 3: the sample size is what matters. The size of the sample determines what we can conclude from the data regardless of the size of the population. Aim to get a representative sample depends of the situation. Representative sample: a sample in which the statistics computed accurately reflect the corresponding population parameters. Census: an attempt to collect data on the entire population of interest.