In this week’s episode Greg and Patrick discuss the critical distinction between sample distributions and sampling distributions and we explore all the different ways in which sampling distributions are foundational to how we conduct research. Along the way they also discuss Starbucks jazz, one item tests, hot pockets, delusions of grandeur, Tetris and Pong, drawing inappropriate distributions, magical properties, texting pictures of kindle pages, Roman arches, 1970’s graphics, never saying never, mumbling, Greenday, ignoring Roy Levy, real life bootstrap, and Goodnight Gracie.
Lightly-Edited Episode Transcript
We provide a lightly-edited and imperfect audio transcript of the episode available here. This is not an exact representation of the audio, but does provide a searchable document with identified speakers and associated time stamps.
Low-Res Sampling Distribution Simulation Applet
Additional Show Notes
Bollen, K. A., & Stine, R. A. (1992). Bootstrapping goodness-of-fit measures in structural equation models. Sociological Methods & Research, 21, 205-229.
Efron, B. (2012). Bayesian inference and the parametric bootstrap. The Annals of Applied Statistics, 6(4), 1971.
Efron, B., & Tibshirani, R. J. (1994). An introduction to the bootstrap. CRC press.
Hancock, G. R., & Liu, M. (2012). Bootstrapping standard errors and data-model fit statistics in structural equation modeling. In R. H. Hoyle (Ed.), Handbook of structural equation modeling (pp. 296–306). The Guilford Press.
Johnson, R. W. (2001). An introduction to the bootstrap. Teaching Satistics, 23, 49-54.
Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40, 879-891.