ARIMA modeling (video 1) in SPSS: model identification

Be sure to visit my website at: https://sites.google.com/view/statistics-for-the-real-world/home This video is the first of several on ARIMA modeling using IBM SPSS. Specifically, it focuses on how to identify AR and MA processes. It also covers the topic of stationarity and identification of trending. (Be sure to check out the next video in the series on estimating ARIMA model parameters using SPSS syntax. Example syntax can be accessed through links in the video description) A copy of the original dataset can be downloaded here: https://drive.google.com/open?id=1gT2FbgUeZHIAG5vKctUrJWM--pbkXWRk The demonstrations provided in this video come from Chapter 18 of Tabachnick & Fidell's text, Using Multivariate Statistics (6th edition; https://www.pearson.com/us/higher-education/program/Tabachnick-Using-Multivariate-Statistics-6th-Edition/PGM332849.html) The chapter is downloadable from the textbook website at: http://media.pearsoncmg.com/ab/ab_tabachnick_multistats_6/datafiles/M18_TABA9574_06_SE_C18.pdf For more details of the computations involved, you can go here: https://youtu.be/WlSz0Ji19PM