One-Sample Models (Continuous DV) Then: Simple Linear Regression P548: Bayesian Stats with Psych Applications Instructor: John Miyamoto 02/27/2017: Lecture 09-1 Note: This Powerpoint presentation may contain macros that I wrote to help me create the slides. The macros aren’t needed to view the slides. You can disable or delete the macros without any change to the presentation.

Extracting R-Code from within a genMCMC Function Definition Look at the function code for the genMCMC function in: Jags-Ymet-Xnom1grp-Mnormal.R It is usually possible to extract the code and run it as if it were not part of a function, i.e., not part of the genMCMC function. The code in demo.09-1.p548.w17.r extracts code from the definition of the genMCMC function in Jags-Ymet-Xnom1grp-Mnormal.R This will let us see what the code is doing. Psych 548, Miyamoto, Win '17

KR (Ed. 2): One Sample Normal Model Kruschke Fig. 16.2 (Ed. 2, p. 455) Left: Gamma prior on precision (1/2) Right: Uniform prior on sigma% UW Psych 548, Miyamoto, Win ###

KR (Ed. 2): One Sample Normal Model i = 1:N yi Priors:  ~ Unif(sdY/1000, sdY*1000)  = 1/2  ~ N(meanY, 1/(100*sdY)2), Likelihood y ~ N(, ) Kruschke Fig. 16.2 (Ed. 2, p. 455) [Omitted] Gamma prior on precision (1/2) Uniform prior on sigma UW Psych 548, Miyamoto, Win ###

Set Up for Instructor Turn off your cell phone. Close web browsers if they are not needed. Classroom Support Services (CSS), 35 Kane Hall, 206-543-9900 If the display is odd, try setting your resolution to 1024 by 768 Run Powerpoint. For most reliable start up: Start laptop & projector before connecting them together If necessary, reboot the laptop Psych 548, Miyamoto, Aut ‘16