Population, sample, estimate, and standard error
Channel: Mikko Rönkkö
Date: 09/07/2019

This video talks about the basic statistical concepts: population, a sample, an estimate and the standard error, which are commonly used in quantitative research. In most instances, gathering information from an entire population isn't feasible due to the scale. Hence, a smaller representative sample is utilized to estimate population parameters. The video underlines the distinction between population and sample, introducing essential concepts such as the margin of error standard error, sample variance, and estimator.

The video uses a hypothetical university scenario to explore these concepts further. It delves into the analysis of different strategies for estimating a population parameter, underlining the importance of understanding how these strategies work to ensure high-quality research. The video categorizes estimators based on consistency, unbiasedness, efficiency, and normality, emphasizing their relevance in carrying out accurate regression analysis. It also examines the trade-offs between biased efficiency and efficient bias, highlighting the need to understand these concepts to make informed choices in research.

Slides: https://osf.io/3q5h6